@articlegirshick2015fast, title=Fast r-cnn, author=Girshick, Ross,
journal=arXiv preprint arXiv:1504.08083, year=2015

@articlekhojasteh2018exudate, title=Exudate detection in fundus images using
deeply-learnable features, author=Khojasteh, Parham and Júnior, Leandro
Aparecido Passos and Carvalho, Tiago and Rezende, Edmar and Aliahmad, Behzad
and Papa, João Paulo and Kumar, Dinesh Kant, journal=Computers in biology and
medicine, year=2018, publisher=Elsevier

@articlewelikala2014automated, title=Automated detection of proliferative
diabetic retinopathy using a modified line operator and dual classification,
author=Welikala, RA and Dehmeshki, Jamshid and Hoppe, Andreas and Tah, V and
Mann, S and Williamson, Thomas H and Barman, SA, journal=Computer methods and
programs in biomedicine, volume=114, number=3, pages=247–261, year=2014,
publisher=Elsevier

@articlechudzik2018microaneurysm1, title=Microaneurysm detection using fully
convolutional neural networks, author=Chudzik, Piotr and Majumdar, Somshubra
and Calivá, Francesco and Al-Diri, Bashir and Hunter, Andrew, journal=Computer
methods and programs in biomedicine, volume=158, pages=185–192, year=2018,
publisher=Elsevier

@articleadal2014automated, title=Automated detection of microaneurysms using
scale-adapted blob analysis and semi-supervised learning, author=Adal, Kedir M
and Sidibé, Désiré and Ali, Sharib and Chaum, Edward and Karnowski, Thomas P
and Mériaudeau, Fabrice, journal=Computer methods and programs in biomedicine,
volume=114, number=1, pages=1–10, year=2014, publisher=Elsevier

@articlelam2008novel, title=A novel vessel segmentation algorithm for
pathological retina images based on the divergence of vector fields,
author=Lam, Benson Shu Yan and Yan, Hong, journal=IEEE Transactions on Medical
Imaging, volume=27, number=2, pages=237–246, year=2008, publisher=IEEE

@articleluo2017understanding, title=Understanding the effective receptive
field in deep convolutional neural networks, author=Luo, Wenjie and Li, Yujia
and Urtasun, Raquel and Zemel, Richard, journal=arXiv preprint
arXiv:1701.04128, year=2017

@articleporwal2020idrid, title=Idrid: Diabetic retinopathy–segmentation and
grading challenge, author=Porwal, Prasanna and Pachade, Samiksha and Kokare,
Manesh and Deshmukh, Girish and Son, Jaemin and Bae, Woong and Liu, Lihong and
Wang, Jianzong and Liu, Xinhui and Gao, Liangxin and others, journal=Medical
image analysis, volume=59, pages=101561, year=2020, publisher=Elsevier

@booksoriano2016diagnostic, title=Diagnostic atlas of retinal diseases,
author=Soriano, Mitzy E Torres and Aguirre, Gerardo García, volume=1,
year=2016, publisher=Bentham Science Publishers

@inproceedingschudzik2018microaneurysm2, title=Microaneurysm detection using
deep learning and interleaved freezing, author=Chudzik, Piotr and Majumdar,
Somshubra and Caliva, Francesco and Al-Diri, Bashir and Hunter, Andrew,
booktitle=Medical Imaging 2018: Image Processing, volume=10574, pages=105741I,
year=2018, organization=International Society for Optics and Photonics

@inproceedingsvan2011segmentation, title=Segmentation as selective search for
object recognition, author=Van de Sande, Koen EA and Uijlings, Jasper RR and
Gevers, Theo and Smeulders, Arnold WM, booktitle=Computer Vision (ICCV), 2011
IEEE International Conference on, pages=1879–1886, year=2011,
organization=IEEE

@articlezhang2014exudate, title=Exudate detection in color retinal images for
mass screening of diabetic retinopathy, author=Zhang, Xiwei and Thibault,
Guillaume and Decencière, Etienne and Marcotegui, Beatriz and Laÿ, Bruno and
Danno, Ronan and Cazuguel, Guy and Quellec, Gwénolé and Lamard, Mathieu and
Massin, Pascale and others, journal=Medical image analysis, volume=18,
number=7, pages=1026–1043, year=2014, publisher=Elsevier

@conferenceGondaletal17, title = Weakly-Supervised Localization of Diabetic
Retinopathy Lesions in Retinal Fundus Images, author = Gondal, W. and Köhler,
J. M. and Grzeszick, R. and Fink, G. and Hirsch, M., booktitle = IEEE
International Conference on Image Processing (ICIP 207), year = 2017

@inproceedingsfleming2008automated, title=Automated detection of blot
haemorrhages as a sign of referable diabetic retinopathy, author=Fleming, AD
and Goatman, KA and Williams, GJ and Philip, S and Sharp, PF and Olson, JA,
booktitle=Proc. Medical Image Understanding and Analysis, year=2008

@inproceedingszhou2016learning, title=Learning deep features for
discriminative localization, author=Zhou, Bolei and Khosla, Aditya and
Lapedriza, Agata and Oliva, Aude and Torralba, Antonio, booktitle=Proceedings
of the IEEE Conference on Computer Vision and Pattern Recognition,
pages=2921–2929, year=2016

@inproceedingsfu2016deepvessel, title=Deepvessel: Retinal vessel segmentation
via deep learning and conditional random field, author=Fu, Huazhu and Xu,
Yanwu and Lin, Stephen and Wong, Damon Wing Kee and Liu, Jiang,
booktitle=International Conference on Medical Image Computing and Computer-
Assisted Intervention, pages=132–139, year=2016, organization=Springer

@articleantal2012ensemble, title=An ensemble-based system for microaneurysm
detection and diabetic retinopathy grading, author=Antal, Balint and Hajdu,
Andras, journal=IEEE transactions on biomedical engineering, volume=59,
number=6, pages=1720–1726, year=2012, publisher=IEEE
@inproceedingsfu2016retinal, title=Retinal vessel segmentation via deep
learning network and fully-connected conditional random fields, author=Fu,
Huazhu and Xu, Yanwu and Wong, Damon Wing Kee and Liu, Jiang,
booktitle=Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium
on, pages=698–701, year=2016, organization=IEEE

@articlemansour2018deep, title=Deep-learning-based automatic computer-aided
diagnosis system for diabetic retinopathy, author=Mansour, Romany F,
journal=Biomedical Engineering Letters, volume=8, number=1, pages=41–57,
year=2018, publisher=Springer

@articlemo2018exudate, title=Exudate-based diabetic macular edema recognition
in retinal images using cascaded deep residual networks, author=Mo, Juan and
Zhang, Lei and Feng, Yangqin, journal=Neurocomputing, volume=290,
pages=161–171, year=2018, publisher=Elsevier

@inproceedingswu2016deep, title=Deep vessel tracking: A generalized
probabilistic approach via deep learning, author=Wu, Aaron and Xu, Ziyue and
Gao, Mingchen and Buty, Mario and Mollura, Daniel J, booktitle=Biomedical
Imaging (ISBI), 2016 IEEE 13th International Symposium on, pages=1363–1367,
year=2016, organization=IEEE

@articlezilly2017glaucoma, title=Glaucoma detection using entropy sampling and
ensemble learning for automatic optic cup and disc segmentation, author=Zilly,
Julian and Buhmann, Joachim M and Mahapatra, Dwarikanath, journal=Computerized
Medical Imaging and Graphics, volume=55, pages=28–41, year=2017,
publisher=Elsevier

@inproceedingslahiri2016deep, title=Deep neural ensemble for retinal vessel
segmentation in fundus images towards achieving label-free angiography,
author=Lahiri, Avisek and Roy, Abhijit Guha and Sheet, Debdoot and Biswas,
Prabir Kumar, booktitle=Engineering in Medicine and Biology Society (EMBC),
2016 IEEE 38th Annual International Conference of the, pages=1340–1343,
year=2016, organization=IEEE

@articleakram2014detection, title=Detection and classification of retinal
lesions for grading of diabetic retinopathy, author=Akram, M Usman and Khalid,
Shehzad and Tariq, Anam and Khan, Shoab A and Azam, Farooque,
journal=Computers in biology and medicine, volume=45, pages=161–171,
year=2014, publisher=Elsevier

@articleakram2013multilayered, title=Multilayered thresholding-based blood
vessel segmentation for screening of diabetic retinopathy, author=Akram, M
Usman and Khan, Shoab A, journal=Engineering with computers, volume=29,
number=2, pages=165–173, year=2013, publisher=Springer

@articlequellec2017deep, title=Deep image mining for diabetic retinopathy
screening, author=Quellec, Gwenolé and Charrière, Katia and Boudi, Yassine and
Cochener, Béatrice and Lamard, Mathieu, journal=Medical Image Analysis,
volume=39, pages=178–193, year=2017, publisher=Elsevier
@inproceedingsmaji2015deep, title=Deep neural network and random forest hybrid
architecture for learning to detect retinal vessels in fundus images,
author=Maji, Debapriya and Santara, Anirban and Ghosh, Sambuddha and Sheet,
Debdoot and Mitra, Pabitra, booktitle=Engineering in Medicine and Biology
Society (EMBC), 2015 37th Annual International Conference of the IEEE,
pages=3029–3032, year=2015, organization=IEEE

@articlesivaswamy2015comprehensive, title=A comprehensive retinal image
dataset for the assessment of glaucoma from the optic nerve head analysis,
author=Sivaswamy, Jayanthi and Krishnadas, S and Chakravarty, Arunava and
Joshi, GD and Tabish, A Syed and others, journal=JSM Biomedical Imaging Data
Papers, volume=2, number=1, pages=1004, year=2015

@inproceedingssivaswamy2014drishti, title=Drishti-gs: Retinal image dataset
for optic nerve head (onh) segmentation, author=Sivaswamy, Jayanthi and
Krishnadas, SR and Joshi, Gopal Datt and Jain, Madhulika and Tabish, A Ujjwaft
Syed, booktitle=Biomedical Imaging (ISBI), 2014 IEEE 11th International
Symposium on, pages=53–56, year=2014, organization=IEEE
@articlezilly2015boosting, title=Boosting convolutional filters with entropy
sampling for optic cup and disc image segmentation from fundus images,
author=Zilly, Julian G and Buhmann, Joachim M and Mahapatra, Dwarikanath,
booktitle=International Workshop on Machine Learning in Medical Imaging,
pages=136–143, year=2015, organization=Springer @articleli2016cross, title=A
cross-modality learning approach for vessel segmentation in retinal images,
author=Li, Qiaoliang and Feng, Bowei and Xie, LinPei and Liang, Ping and
Zhang, Huisheng and Wang, Tianfu, journal=IEEE transactions on medical
imaging, volume=35, number=1, pages=109–118, year=2016, publisher=IEEE

@articlemaji2016ensemble, title=Ensemble of deep convolutional neural networks
for learning to detect retinal vessels in fundus images, author=Maji,
Debapriya and Santara, Anirban and Mitra, Pabitra and Sheet, Debdoot,
journal=arXiv preprint arXiv:1603.04833, year=2016

@articleli2016cross, title=A cross-modality learning approach for vessel
segmentation in retinal images, author=Li, Qiaoliang and Feng, Bowei and Xie,
LinPei and Liang, Ping and Zhang, Huisheng and Wang, Tianfu, journal=IEEE
transactions on medical imaging, volume=35, number=1, pages=109–118,
year=2016, publisher=IEEE

@inproceedingsxie2017aggregated, title=Aggregated residual transformations for
deep neural networks, author=Xie, Saining and Girshick, Ross and Dollár, Piotr
and Tu, Zhuowen and He, Kaiming, booktitle=Proceedings of the IEEE conference
on computer vision and pattern recognition, pages=1492–1500, year=2017

@articlelim2015integrated, title=Integrated optic disc and cup segmentation
with deep learning, author=Lim, Gilbert and Cheng, Yuan and Hsu, Wynne and
Lee, Mong Li, booktitle=Tools with Artificial Intelligence (ICTAI), 2015 IEEE
27th International Conference on, pages=162–169, year=2015, organization=IEEE

@articleabbas2017glaucoma, title=Glaucoma-Deep: Detection of Glaucoma Eye
Disease on Retinal Fundus Images using Deep Learning, author=Abbas, Qaisar,
journal=INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS,
volume=8, number=6, pages=41–45, year=2017, publisher=SCIENCE & INFORMATION
SAI ORGANIZATION LTD 19 BOLLING RD, BRADFORD, WEST YORKSHIRE, 00000, ENGLAND

@inproceedingsorlando2017convolutional, title=Convolutional neural network
transfer for automated glaucoma identification, author=Orlando, José Ignacio
and Prokofyeva, Elena and del Fresno, Mariana and Blaschko, Matthew B,
booktitle=12th International Symposium on Medical Information Processing and
Analysis, volume=10160, pages=101600U, year=2017, organization=International
Society for Optics and Photonics

@inproceedingssedai2017semi, title=Semi-supervised Segmentation of Optic Cup
in Retinal Fundus Images Using Variational Autoencoder, author=Sedai, Suman
and Mahapatra, Dwarikanath and Hewavitharanage, Sajini and Maetschke, Stefan
and Garnavi, Rahil, booktitle=International Conference on Medical Image
Computing and Computer-Assisted Intervention, pages=75–82, year=2017,
organization=Springer

@articletan2017segmentation, title=Segmentation of optic disc, fovea and
retinal vasculature using a single convolutional neural network, author=Tan,
Jen Hong and Acharya, U Rajendra and Bhandary, Sulatha V and Chua, Kuang Chua
and Sivaprasad, Sobha, journal=Journal of Computational Science, volume=20,
pages=70–79, year=2017, publisher=Elsevier

@inproceedingssedai2017semi, title=Semi-supervised Segmentation of Optic Cup
in Retinal Fundus Images Using Variational Autoencoder, author=Sedai, Suman
and Mahapatra, Dwarikanath and Hewavitharanage, Sajini and Maetschke, Stefan
and Garnavi, Rahil, booktitle=International Conference on Medical Image
Computing and Computer-Assisted Intervention, pages=75–82, year=2017,
organization=Springer

@incollectionshankaranarayana2017joint, title=Joint Optic Disc and Cup
Segmentation Using Fully Convolutional and Adversarial Networks,
author=Shankaranarayana, Sharath M and Ram, Keerthi and Mitra, Kaushik and
Sivaprakasam, Mohanasankar, booktitle=Fetal, Infant and Ophthalmic Medical
Image Analysis, pages=168–176, year=2017, publisher=Springer
@articlefu2018joint, title=Joint optic disc and cup segmentation based on
multi-label deep network and polar transformation, author=Fu, Huazhu and
Cheng, Jun and Xu, Yanwu and Wong, Damon Wing Kee and Liu, Jiang and Cao,
Xiaochun, journal=arXiv preprint arXiv:1801.00926, year=2018

@articlevan2016fast, title=Fast convolutional neural network training using
selective data sampling: Application to hemorrhage detection in color fundus
images, author=van Grinsven, Mark JJP and van Ginneken, Bram and Hoyng, Carel
B and Theelen, Thomas and Sánchez, Clara I, journal=IEEE transactions on
medical imaging, volume=35, number=5, pages=1273–1284, year=2016,
publisher=IEEE

@inproceedingsnugroho2015automated, title=Automated segmentation of optic disc
area using mathematical morphology and active contour, author=Nugroho, Hanung
Adi and Listyalina, Latifah and Setiawan, Noor Akhmad and Wibirama, Sunu and
Dharmawan, Dhimas Arief, booktitle=Computer, Control, Informatics and its
Applications (IC3INA), 2015 International Conference on, pages=18–22,
year=2015, organization=IEEE

@inproceedingsakram2010retinal, title=Retinal images: optic disk localization
and detection, author=Akram, M Usman and Khan, Aftab and Iqbal, Khalid and
Butt, Wasi Haider, booktitle=International Conference Image Analysis and
Recognition, pages=40–49, year=2010, organization=Springer

@articledevasia2015automatic, title=Automatic Extraction and Localisation of
Optic Disc in Colour Fundus Images, author=Devasia, Thresiamma and Jacob,
Poulose and Thomas, Tessamma, journal=International Journal of Computer
Science Issues (IJCSI), volume=12, number=3, pages=146, year=2015,
publisher=International Journal of Computer Science Issues (IJCSI)

@inproceedingsqureshi2012automatic, title=Automatic localization of the optic
disc in retinal fundus images using multiple features, author=Qureshi, Touseef
Ahmad and Amin, Hassan and Hussain, Mahfooz and Qureshi, Rashid Jalal and Al-
Diri, Bashir, booktitle=Bioinformatics & Bioengineering (BIBE), 2012 IEEE 12th
International Conference on, pages=488–493, year=2012, organization=IEEE

@inproceedingsronneberger2015u, title=U-net: Convolutional networks for
biomedical image segmentation, author=Ronneberger, Olaf and Fischer, Philipp
and Brox, Thomas, booktitle=International Conference on Medical image
computing and computer-assisted intervention, pages=234–241, year=2015,
organization=Springer

@inproceedingsniu2017automatic, title=Automatic localization of optic disc
based on deep learning in fundus images, author=Niu, Di and Xu, Peiyuan and
Wan, Cheng and Cheng, Jun and Liu, Jiang, booktitle=Signal and Image
Processing (ICSIP), 2017 IEEE 2nd International Conference on, pages=208–212,
year=2017, organization=IEEE

@articleprentavsic2016segmentation, title=Segmentation of the foveal
microvasculature using deep learning networks, author=Prentašić, Pavle and
Heisler, Morgan and Mammo, Zaid and Lee, Sieun and Merkur, Andrew and Navajas,
Eduardo and Beg, Mirza Faisal and Šarunic, Marinko and Lončarić, Sven,
journal=Journal of biomedical optics, volume=21, number=7, pages=075008,
year=2016, publisher=International Society for Optics and Photonics

@articlelitjens2017survey, title=A survey on deep learning in medical image
analysis, author=Litjens, Geert and Kooi, Thijs and Bejnordi, Babak Ehteshami
and Setio, Arnaud Arindra Adiyoso and Ciompi, Francesco and Ghafoorian, Mohsen
and van der Laak, Jeroen AWM and van Ginneken, Bram and Sánchez, Clara I,
journal=Medical image analysis, volume=42, pages=60–88, year=2017,
publisher=Elsevier

@articlelecun1998gradient, title=Gradient-based learning applied to document
recognition, author=LeCun, Yann and Bottou, Léon and Bengio, Yoshua and
Haffner, Patrick, journal=Proceedings of the IEEE, volume=86, number=11,
pages=2278–2324, year=1998, publisher=IEEE

@inproceedingskrizhevsky2012imagenet, title=Imagenet classification with deep
convolutional neural networks, author=Krizhevsky, Alex and Sutskever, Ilya and
Hinton, Geoffrey E, booktitle=Advances in neural information processing
systems, pages=1097–1105, year=2012

@inproceedingssetiawan2013color, title=Color retinal image enhancement using
CLAHE, author=Setiawan, Agung W and Mengko, Tati R and Santoso, Oerip S and
Suksmono, Andriyan B, booktitle=International Conference on ICT for Smart
Society, pages=1–3, year=2013, organization=IEEE

@articlesimonyan2014very, title=Very deep convolutional networks for large-
scale image recognition, author=Simonyan, Karen and Zisserman, Andrew,
journal=arXiv preprint arXiv:1409.1556, year=2014

@articlegu2018recent, title=Recent advances in convolutional neural networks,
author=Gu, Jiuxiang and Wang, Zhenhua and Kuen, Jason and Ma, Lianyang and
Shahroudy, Amir and Shuai, Bing and Liu, Ting and Wang, Xingxing and Wang,
Gang and Cai, Jianfei and others, journal=Pattern Recognition, volume=77,
pages=354–377, year=2018, publisher=Elsevier

@inproceedingsszegedy2015going, title=Going deeper with convolutions,
author=Szegedy, Christian and Liu, Wei and Jia, Yangqing and Sermanet, Pierre
and Reed, Scott and Anguelov, Dragomir and Erhan, Dumitru and Vanhoucke,
Vincent and Rabinovich, Andrew and others, year=2015, organization=Cvpr

@inproceedingshe2016deep, title=Deep residual learning for image recognition,
author=He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian,
booktitle=Proceedings of the IEEE conference on computer vision and pattern
recognition, pages=770–778, year=2016

@articleprentavsic2016detection, title=Detection of exudates in fundus
photographs using deep neural networks and anatomical landmark detection
fusion, author=Prentašić, Pavle and Lončarić, Sven, journal=Computer methods
and programs in biomedicine, volume=137, pages=281–292, year=2016,
publisher=Elsevier @inproceedingsprentavsic2015detection, title=Detection of
exudates in fundus photographs using convolutional neural networks,
author=Prentašić, Pavle and Lončarić, Sven, booktitle=Image and Signal
Processing and Analysis (ISPA), 2015 9th International Symposium on,
pages=188–192, year=2015, organization=IEEE

@articlearunkumar2017multi, title=Multi-retinal disease classification by
reduced deep learning features, author=Arunkumar, R and Karthigaikumar, P,
journal=Neural Computing and Applications, volume=28, number=2, pages=329–334,
year=2017, publisher=Springer

@inproceedingschen2015glaucoma, title=Glaucoma detection based on deep
convolutional neural network, author=Chen, Xiangyu and Xu, Yanwu and Wong,
Damon Wing Kee and Wong, Tien Yin and Liu, Jiang, booktitle=Engineering in
Medicine and Biology Society (EMBC), 2015 37th Annual International Conference
of the IEEE, pages=715–718, year=2015, organization=IEEE

@inproceedingsburlina2016detection, title=Detection of age-related macular
degeneration via deep learning, author=Burlina, Philippe and Freund, David E
and Joshi, Neil and Wolfson, Y and Bressler, Neil M, booktitle=Biomedical
Imaging (ISBI), 2016 IEEE 13th International Symposium on, pages=184–188,
year=2016, organization=IEEE

@articlesevik2014identification, title=Identification of suitable fundus
images using automated quality assessment methods, author=Sevik, Ugur and
Kose, Cemal and Berber, Tolga and Erdol, Hidayet, journal=Journal of
biomedical optics, volume=19, number=4, pages=046006, year=2014,
publisher=International Society for Optics and Photonics

@articlezhao2019object, title=Object detection with deep learning: A review,
author=Zhao, Zhong-Qiu and Zheng, Peng and Xu, Shou-tao and Wu, Xindong,
journal=IEEE transactions on neural networks and learning systems, volume=30,
number=11, pages=3212–3232, year=2019, publisher=IEEE

@articlesimonyan2014very, title=Very deep convolutional networks for large-
scale image recognition, author=Simonyan, Karen and Zisserman, Andrew,
journal=arXiv preprint arXiv:1409.1556, year=2014

@articlehwang2016self, title=Self-transfer learning for fully weakly
supervised object localization, author=Hwang, Sangheum and Kim, Hyo-Eun,
journal=arXiv preprint arXiv:1602.01625, year=2016

@inproceedingsworrall2016automated, title=Automated retinopathy of prematurity
case detection with convolutional neural networks, author=Worrall, Daniel E
and Wilson, Clare M and Brostow, Gabriel J, booktitle=International Workshop
on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis,
pages=68–76, year=2016, organization=Springer

@articlecolas2016deep, title=Deep learning approach for diabetic retinopathy
screening, author=Colas, E and Besse, A and Orgogozo, A and Schmauch, B and
Meric, N and Besse, E, journal=Acta Ophthalmologica, volume=94, number=S256,
year=2016, publisher=Wiley Online Library

@articlepratt2016convolutional, title=Convolutional neural networks for
diabetic retinopathy, author=Pratt, Harry and Coenen, Frans and Broadbent,
Deborah M and Harding, Simon P and Zheng, Yalin, journal=Procedia Computer
Science, volume=90, pages=200–205, year=2016, publisher=Elsevier

@articlesahiner1996classification, title=Classification of mass and normal
breast tissue: a convolution neural network classifier with spatial domain and
texture images, author=Sahiner, Berkman and Chan, Heang-Ping and Petrick,
Nicholas and Wei, Datong and Helvie, Mark A and Adler, Dorit D and Goodsitt,
Mitchell M, journal=IEEE transactions on Medical Imaging, volume=15, number=5,
pages=598–610, year=1996, publisher=IEEE

@articlegargeya2017automated, title=Automated identification of diabetic
retinopathy using deep learning, author=Gargeya, Rishab and Leng, Theodore,
journal=Ophthalmology, volume=124, number=7, pages=962–969, year=2017,
publisher=Elsevier

@articleerhan2010does, title=Why does unsupervised pre-training help deep
learning?, author=Erhan, Dumitru and Bengio, Yoshua and Courville, Aaron and
Manzagol, Pierre-Antoine and Vincent, Pascal and Bengio, Samy, journal=Journal
of Machine Learning Research, volume=11, number=Feb, pages=625–660, year=2010

@articlevinyals2017show, title=Show and tell: Lessons learned from the 2015
mscoco image captioning challenge, author=Vinyals, Oriol and Toshev, Alexander
and Bengio, Samy and Erhan, Dumitru, journal=IEEE transactions on pattern
analysis and machine intelligence, volume=39, number=4, pages=652–663,
year=2017, publisher=IEEE

@articlehinton2006reducing, title=Reducing the dimensionality of data with
neural networks, author=Hinton, Geoffrey E and Salakhutdinov, Ruslan R,
journal=science, volume=313, number=5786, pages=504–507, year=2006,
publisher=American Association for the Advancement of Science

@articletajbakhsh2016convolutional, title=Convolutional neural networks for
medical image analysis: Full training or fine tuning?, author=Tajbakhsh, Nima
and Shin, Jae Y and Gurudu, Suryakanth R and Hurst, R Todd and Kendall,
Christopher B and Gotway, Michael B and Liang, Jianming, journal=IEEE
transactions on medical imaging, volume=35, number=5, pages=1299–1312,
year=2016, publisher=IEEE @inproceedingslong2015fully, title=Fully
convolutional networks for semantic segmentation, author=Long, Jonathan and
Shelhamer, Evan and Darrell, Trevor, booktitle=Proceedings of the IEEE
conference on computer vision and pattern recognition, pages=3431–3440,
year=2015 @articlegulshan2016development, title=Development and validation of
a deep learning algorithm for detection of diabetic retinopathy in retinal
fundus photographs, author=Gulshan, Varun and Peng, Lily and Coram, Marc and
Stumpe, Martin C and Wu, Derek and Narayanaswamy, Arunachalam and Venugopalan,
Subhashini and Widner, Kasumi and Madams, Tom and Cuadros, Jorge and others,
journal=Jama, volume=316, number=22, pages=2402–2410, year=2016,
publisher=American Medical Association

@articlecosta2017convolutional, title=Convolutional bag of words for diabetic
retinopathy detection from eye fundus images, author=Costa, Pedro and
Campilho, Aurélio, journal=IPSJ Transactions on Computer Vision and
Applications, volume=9, number=1, pages=10, year=2017, publisher=Springer
Berlin Heidelberg

@articlesoares2006retinal, title=Retinal vessel segmentation using the 2-D
Gabor wavelet and supervised classification, author=Soares, João VB and
Leandro, Jorge JG and Cesar, Roberto M and Jelinek, Herbert F and Cree,
Michael J, journal=IEEE Transactions on medical Imaging, volume=25, number=9,
pages=1214–1222, year=2006, publisher=IEEE

@inproceedings13, title=Beyond bags of features: Spatial pyramid matching for
recognizing natural scene categories, author=Lazebnik, Svetlana and Schmid,
Cordelia and Ponce, Jean, booktitle=Computer vision and pattern recognition,
2006 IEEE computer society conference on, volume=2, pages=2169–2178,
year=2006, organization=IEEE

@inproceedingshuang2017speed, title=Speed/accuracy trade-offs for modern
convolutional object detectors, author=Huang, Jonathan and Rathod, Vivek and
Sun, Chen and Zhu, Menglong and Korattikara, Anoop and Fathi, Alireza and
Fischer, Ian and Wojna, Zbigniew and Song, Yang and Guadarrama, Sergio and
others, booktitle=Proceedings of the IEEE conference on computer vision and
pattern recognition, pages=7310–7311, year=2017

@inproceedings6, title=What does classifying more than 10,000 image categories
tell us?, author=Deng, Jia and Berg, Alexander C and Li, Kai and Fei-Fei, Li,
booktitle=European conference on computer vision, pages=71–84, year=2010,
organization=Springer

@inproceedings9, title=The pyramid match kernel: Discriminative classification
with sets of image features, author=Grauman, Kristen and Darrell, Trevor,
booktitle=Computer Vision, 2005. ICCV 2005. Tenth IEEE International
Conference on, volume=2, pages=1458–1465, year=2005, organization=IEEE

@article11, title=Design of effective neural network ensembles for image
classification purposes, author=Giacinto, Giorgio and Roli, Fabio,
journal=Image and Vision Computing, volume=19, number=9, pages=699–707,
year=2001, publisher=Elsevier @articlepatton2006retinal, title=Retinal image
analysis: concepts, applications and potential, author=Patton, Niall and
Aslam, Tariq M and MacGillivray, Thomas and Deary, Ian J and Dhillon, Baljean
and Eikelboom, Robert H and Yogesan, Kanagasingam and Constable, Ian J,
journal=Progress in retinal and eye research, volume=25, number=1,
pages=99–127, year=2006, publisher=Elsevier @articleasiri2019deep, title=Deep
learning based computer-aided diagnosis systems for diabetic retinopathy: A
survey, author=Asiri, Norah and Hussain, Muhammad and Al Adel, Fadwa and
Alzaidi, Nazih, journal=Artificial Intelligence in Medicine, year=2019,
publisher=Elsevier

@articlewinder2009algorithms, title=Algorithms for digital image processing in
diabetic retinopathy, author=Winder, Robert John and Morrow, Philip J and
McRitchie, Ian N and Bailie, JR and Hart, Patricia M, journal=Computerized
medical imaging and graphics, volume=33, number=8, pages=608–622, year=2009,
publisher=Elsevier @article2, title=High-order distance-based multiview
stochastic learning in image classification, author=Yu, Jun and Rui, Yong and
Tang, Yuan Yan and Tao, Dacheng, journal=IEEE transactions on cybernetics,
volume=44, number=12, pages=2431–2442, year=2014, publisher=IEEE
@articlealwin2017type, title=Type 2 Diabetes Mellitus in Saudi Arabia: Major
Challenges and Possible Solutions, author=Alwin Robert, Asirvatham and
Abdulaziz Al Dawish, Mohamed and Braham, Rim and Ali Musallam, Maha and
Abdullah Al Hayek, Ayman and Hazza Al Kahtany, Nasser, journal=Current
diabetes reviews, volume=13, number=1, pages=59–64, year=2017,
publisher=Bentham Science Publishers

@articlewilkinson2003proposed, title=Proposed international clinical diabetic
retinopathy and diabetic macular edema disease severity scales,
author=Wilkinson, CP and Ferris, Frederick L and Klein, Ronald E and Lee, Paul
P and Agardh, Carl David and Davis, Matthew and Dills, Diana and Kampik,
Anselm and Pararajasegaram, R and Verdaguer, Juan T and others,
journal=Ophthalmology, volume=110, number=9, pages=1677–1682, year=2003,
publisher=Elsevier

@articlegupta2017local, title=Local characterization of neovascularization and
identification of proliferative diabetic retinopathy in retinal fundus images,
author=Gupta, Garima and Kulasekaran, S and Ram, Keerthi and Joshi, Niranjan
and Sivaprakasam, Mohanasankar and Gandhi, Rashmin, journal=Computerized
Medical Imaging and Graphics, volume=55, pages=124–132, year=2017,
publisher=Elsevier

@inproceedingszhou2016learning, title=Learning deep features for
discriminative localization, author=Zhou, Bolei and Khosla, Aditya and
Lapedriza, Agata and Oliva, Aude and Torralba, Antonio, booktitle=Proceedings
of the IEEE Conference on Computer Vision and Pattern Recognition,
pages=2921–2929, year=2016

@articleli2017robust, title=Robust Retinal Blood Vessel Segmentation Based on
Reinforcement Local Descriptions, author=Li, Meng and Ma, Zhenshen and Liu,
Chao and Zhang, Guang and Han, Zhe, journal=BioMed research international,
volume=2017, year=2017, publisher=Hindawi Publishing Corporation

@articlesoomro2017contrast, title=Contrast normalization steps for increased
sensitivity of a retinal image segmentation method, author=Soomro, Toufique
Ahmed and Khan, Mohammad AU and Gao, Junbin and Khan, Tariq M and Paul,
Manoranjan, journal=Signal, Image and Video Processing, pages=1–9, year=2017,
publisher=Springer

@articlewold1987principal, title=Principal component analysis, author=Wold,
Svante and Esbensen, Kim and Geladi, Paul, journal=Chemometrics and
intelligent laboratory systems, volume=2, number=1-3, pages=37–52, year=1987,
publisher=Elsevier

@inproceedingschen2018diabetic, title=Diabetic Retinopathy Detection Based on
Deep Convolutional Neural Networks, author=Chen, Yi-Wei and Wu, Tung-Yu and
Wong, Wing-Hung and Lee, Chen-Yi, booktitle=2018 IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP), pages=1030–1034,
year=2018, organization=IEEE

@inproceedingswang2017zoom, title=Zoom-in-Net: Deep Mining Lesions for
Diabetic Retinopathy Detection, author=Wang, Zhe and Yin, Yanxin and Shi,
Jianping and Fang, Wei and Li, Hongsheng and Wang, Xiaogang,
booktitle=International Conference on Medical Image Computing and Computer-
Assisted Intervention, pages=267–275, year=2017, organization=Springer

@inproceedingsdr-grades, title=Diabetic retinopathy (DR): management and
referral, booktitle=Community Eye Health, pages=70–71, year=2015

@inproceedingspaing2016detection, title=Detection of lesions and
classification of diabetic retinopathy using fundus images, author=Paing, May
Phu and Choomchuay, Somsak and Yodprom, MD Rapeeporn, booktitle=Biomedical
Engineering International Conference (BMEiCON), 2016 9th, pages=1–5,
year=2016, organization=IEEE

@articleyun2008identification, title=Identification of different stages of
diabetic retinopathy using retinal optical images, author=Yun, Wong Li and
Acharya, U Rajendra and Venkatesh, Yedatore V and Chee, Caroline and Min, Lim
Choo and Ng, E Yin Kwee, journal=Information sciences, volume=178, number=1,
pages=106–121, year=2008, publisher=Elsevier

@bookkertes2007evidence, title=Evidence-based eye care, author=Kertes, Peter J
and Johnson, Thomas Mark, year=2007, publisher=Lippincott Williams & Wilkins
@miscdr, title = Diabetic retinopathy, howpublished =
https://www.nhs.uk/conditions/diabetic-retinopathy/stages/, note = Accessed:
2018-01-08

@miscmessidor, title = Messidor dataset, howpublished =
http://www.adcis.net/en/Download-Third-Party/Messidor.html, note = Accessed:
2018-01-08

@miscoptha, title = E-Ophtha, howpublished = http://www.adcis.net/en/Download-
Third-Party/E-Ophtha.html, note = Accessed: 2018-01-08

@incollectionsimard1998transformation, title=Transformation invariance in
pattern recognition—tangent distance and tangent propagation, author=Simard,
Patrice Y and LeCun, Yann A and Denker, John S and Victorri, Bernard,
booktitle=Neural networks: tricks of the trade, pages=239–274, year=1998,
publisher=Springer @articlerowley1998neural, title=Neural network-based face
detection, author=Rowley, Henry A and Baluja, Shumeet and Kanade, Takeo,
journal=IEEE Transactions on pattern analysis and machine intelligence,
volume=20, number=1, pages=23–38, year=1998, publisher=IEEE

@misckgl, title = Kaggle Dataset, howpublished =
https://www.kaggle.com/c/diabetic-retinopathy-detection/data, note = Accessed:
2018-01-08

@mischrf, title = HRF Dataset, howpublished =
https://www5.cs.fau.de/research/data/fundus-images/, note = Accessed:
2018-04-30

@articlelecun1989backpropagation, title=Backpropagation applied to handwritten
zip code recognition, author=LeCun, Yann and Boser, Bernhard and Denker, John
S and Henderson, Donnie and Howard, Richard E and Hubbard, Wayne and Jackel,
Lawrence D, journal=Neural computation, volume=1, number=4, pages=541–551,
year=1989, publisher=MIT Press

@inproceedingskrizhevsky2012imagenet, title=Imagenet classification with deep
convolutional neural networks, author=Krizhevsky, Alex and Sutskever, Ilya and
Hinton, Geoffrey E, booktitle=Advances in neural information processing
systems, pages=1097–1105, year=2012

@miscidrid, title = IDRiD Dataset, howpublished = https://idrid.grand-
challenge.org/localisation/, note = Accessed: 2018-04-30

@miscdrion, title = drion Dataset, howpublished = http://www.ia.uned.es/
ejcarmona/DRIONS-DB.html, note = Accessed: 2018-04-30

@articlefan2018optic, title=Optic Disk Detection in Fundus Image Based on
Structured Learning, author=Fan, Zhun and Rong, Yibiao and Cai, Xinye and Lu,
Jiewei and Li, Wenji and Lin, Huibiao and Chen, Xinjian, journal=IEEE journal
of biomedical and health informatics, volume=22, number=1, pages=224–234,
year=2018, publisher=IEEE

@articlewalter2002contribution, title=A contribution of image processing to
the diagnosis of diabetic retinopathy-detection of exudates in color fundus
images of the human retina, author=Walter, Thomas and Klein, J-C and Massin,
Pascale and Erginay, Ali, journal=IEEE transactions on medical imaging,
volume=21, number=10, pages=1236–1243, year=2002, publisher=IEEE

@misconhsd, title = ONHSD Dataset images, howpublished =
http://www.aldiri.info/Imagenote = Accessed: 2018-02-13

@misckgl2, title = Kaggle Dataset images classes, howpublished =
http://blog.kaggle.com/2015/08/10/detecting-diabetic-retinopathy-in-eye-
images/, note = Accessed: 2018-02-13

@articlekhojasteh2018exudate, title=Exudate detection in fundus images using
deeply-learnable features, author=Khojasteh, Parham and Júnior, Leandro
Aparecido Passos and Carvalho, Tiago and Rezende, Edmar and Aliahmad, Behzad
and Papa, João Paulo and Kumar, Dinesh Kant, journal=Computers in Biology and
Medicine, year=2018, publisher=Elsevier

@miscdrive, title = DRIVE Dataset, howpublished =
https://www.isi.uu.nl/Research/Databases/DRIVE/, note = Accessed: 2018-01-08

@mischei-med, title = HEI-MED Dataset, howpublished =
http://www.genenetwork.org/dbdoc/Eye_M2_0908_R.html, note = Accessed:
2018-11-02

@miscdrive2, title = DRIVE Dataset, howpublished =
https://www.isi.uu.nl/Research/Databases/DRIVE/results.php, note = Accessed:
2018-01-08

@miscaria, title = ARIA Dataset, howpublished =
http://www.eyecharity.com/aria_online.html, note = Accessed: 2018-02-28

@misceyepacs, title = EyePACS Dataset, howpublished =
http://www.eyepacs.com/eyepacssystem/, note = Accessed: 2018-03-01

@articlehoover2000locating, title=Locating blood vessels in retinal images by
piecewise threshold probing of a matched filter response, author=Hoover, AD
and Kouznetsova, Valentina and Goldbaum, Michael, journal=IEEE Transactions on
Medical imaging, volume=19, number=3, pages=203–210, year=2000, publisher=IEEE

@miscdia, title = DIARETDB1 Dataset, howpublished =
http://www.it.lut.fi/project/imageret/diaretdb1/, note = Accessed: 2018-01-08

@inproceedingshe2016deep, title=Deep residual learning for image recognition,
author=He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian,
booktitle=Proceedings of the IEEE conference on computer vision and pattern
recognition, pages=770–778, year=2016 @articlemo2017multi, title=Multi-level
deep supervised networks for retinal vessel segmentation, author=Mo, Juan and
Zhang, Lei, journal=International journal of computer assisted radiology and
surgery, volume=12, number=12, pages=2181–2193, year=2017, publisher=Springer

@articlezachariah2015grading, title=Grading diabetic retinopathy (DR) using
the Scottish grading protocol, author=Zachariah, Sonia and Wykes, William and
Yorston, David, journal=Community eye health, volume=28, number=92, pages=72,
year=2015, publisher=International Centre for Eye Health

@inproceedingskalviainen2007diaretdb1, title=DIARETDB1 diabetic retinopathy
database and evaluation protocol, author=Kälviäinen, RVJPH and Uusitalo, H,
booktitle=Medical Image Understanding and Analysis, volume=2007, pages=61,
year=2007, organization=Citeseer

@miscchase, title = CHASE Dataset, howpublished =
http://www.chasestudy.ac.uk/, note = Accessed: 2018-02-01

@miscrocds, title = ROC Dataset, howpublished =
http://webeye.ophth.uiowa.edu/ROC/, note = Accessed: 2019-10-3

@bookkanski2009clinical, title=Clinical ophthalmology: a synopsis,
author=Kanski, Jack J, year=2009, publisher=Elsevier Health Sciences

@miscdr_grading, title = Diabetic Retinal Screening, Grading, Monitoring and
Referral Guidance , howpublished =
https://www.health.govt.nz/publication/diabetic-retinal-screening-grading-
monitoring-and-referral-guidance, note = Accessed: 2019-05-01

@articlezhou2017automated, title=Automated Detection of Red Lesions Using
Superpixel Multichannel Multifeature, author=Zhou, Wei and Wu, Chengdong and
Chen, Dali and Wang, Zhenzhu and Yi, Yugen and Du, Wenyou,
journal=Computational and mathematical methods in medicine, volume=2017,
year=2017, publisher=Hindawi

@articlelin2002sensitivity, title=The sensitivity and specificity of single-
field nonmydriatic monochromatic digital fundus photography with remote image
interpretation for diabetic retinopathy screening: a comparison with
ophthalmoscopy and standardized mydriatic color photography, author=Lin, Danny
Y and Blumenkranz, Mark S and Brothers, Rosemary J and Grosvenor, David M and
Group, The Digital Diabetic Screening, journal=American journal of
ophthalmology, volume=134, number=2, pages=204–213, year=2002,
publisher=Elsevier

@inproceedingsprentasic2013diabetic, title=Diabetic retinopathy image database
(DRiDB): a new database for diabetic retinopathy screening programs research,
author=Prentasic, Pavle and Loncaric, Sven and Vatavuk, Zoran and Bencic,
Goran and Subasic, Marko and Petkovic, Tomislav and Dujmovic, Lana and
Malenica-Ravlic, Maja and Budimlija, Nikolina and Tadic, Raseljka,
booktitle=Image and Signal Processing and Analysis (ISPA), 2013 8th
International Symposium on, pages=711–716, year=2013, organization=IEEE

@inproceedingszhang2010origa, title=Origa-light: An online retinal fundus
image database for glaucoma analysis and research, author=Zhang, Zhuo and Yin,
Feng Shou and Liu, Jiang and Wong, Wing Kee and Tan, Ngan Meng and Lee, Beng
Hai and Cheng, Jun and Wong, Tien Yin, booktitle=Engineering in Medicine and
Biology Society (EMBC), 2010 Annual International Conference of the IEEE,
pages=3065–3068, year=2010, organization=IEEE

@articlesng2012determinants, title=Determinants of anterior chamber depth: the
Singapore Chinese Eye Study, author=Sng, Chelvin C and Foo, Li-Lian and Cheng,
Ching-Yu and Allen, John C and He, Mingguang and Krishnaswamy, Gita and
Nongpiur, Monisha E and Friedman, David S and Wong, Tien Y and Aung, Tin,
journal=Ophthalmology, volume=119, number=6, pages=1143–1150, year=2012,
publisher=Elsevier

@miscnih, title = NIH AREDS Dataset, howpublished = https://www.nih.gov/news-
events/news-releases/nih-adds-first-images-major-research-database, note =
Accessed: 2018-02-01

@articlemcleod2005cotton, title=Why cotton wool spots should not be regarded
as retinal nerve fibre layer infarcts, author=McLeod, D, journal=British
journal of ophthalmology, volume=89, number=2, pages=229–237, year=2005,
publisher=BMJ Publishing Group Ltd

@articleharney2006diabetic, title=Diabetic Retinopathy, author=Harney, Fiona,
journal=Medicine, volume=34, number=3, pages=95–98, year=2006,
publisher=Elsevier

@inproceedingshe2016deep, title=Deep residual learning for image recognition,
author=He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian,
booktitle=Proceedings of the IEEE conference on computer vision and pattern
recognition, pages=770–778, year=2016

@articleearly1991grading, title=Grading diabetic retinopathy from stereoscopic
color fundus photographs—an extension of the modified Airlie House
classification: ETDRS report number 10, author=Early Treatment Diabetic
Retinopathy Study Research Group and others, journal=Ophthalmology, volume=98,
number=5, pages=786–806, year=1991, publisher=Elsevier

@articlepatz1980studies, title=Studies on retinal neovascularization.
Friedenwald Lecture., author=Patz, Arnall, journal=Investigative ophthalmology
& visual science, volume=19, number=10, pages=1133–1138, year=1980,
publisher=The Association for Research in Vision and Ophthalmology

@articlemookiah2013computer, title=Computer-aided diagnosis of diabetic
retinopathy: A review, author=Mookiah, Muthu Rama Krishnan and Acharya, U
Rajendra and Chua, Chua Kuang and Lim, Choo Min and Ng, EYK and Laude,
Augustinus, journal=Computers in biology and medicine, volume=43, number=12,
pages=2136–2155, year=2013, publisher=Elsevier

@articlevan1995elevated, title=Elevated glucose levels increase retinal
glycolysis and sorbitol pathway metabolism. Implications for diabetic
retinopathy., author=Van den Enden, Maria K and Nyengaard, Jens R and Ostrow,
Eva and Burgan, Judith H and Williamson, Joseph R, journal=Investigative
ophthalmology & visual science, volume=36, number=8, pages=1675–1685,
year=1995, publisher=The Association for Research in Vision and Ophthalmology

@articleabramoff2010retinal, title=Retinal imaging and image analysis,
author=Abràmoff, Michael D and Garvin, Mona K and Sonka, Milan, journal=IEEE
reviews in biomedical engineering, volume=3, pages=169–208, year=2010,
publisher=IEEE

@articlejoshi2011optic, title=Optic disk and cup segmentation from monocular
color retinal images for glaucoma assessment, author=Joshi, Gopal Datt and
Sivaswamy, Jayanthi and Krishnadas, SR, journal=IEEE transactions on medical
imaging, volume=30, number=6, pages=1192–1205, year=2011, publisher=IEEE

@articlejonas1988optic, title=Optic disk morphometry in high myopia,
author=Jonas, Jost B and Gusek, Gabriele Ch and Naumann, Gottfried OH,
journal=Graefe’s archive for clinical and experimental ophthalmology,
volume=226, number=6, pages=587–590, year=1988, publisher=Springer

@articlenayak2008automated, title=Automated identification of diabetic
retinopathy stages using digital fundus images, author=Nayak, Jagadish and
Bhat, P Subbanna and Acharya, Rajendra and Lim, Choo M and Kagathi, Manjunath,
journal=Journal of medical systems, volume=32, number=2, pages=107–115,
year=2008, publisher=Springer

@inproceedingsneff2017generative, title=Generative Adversarial Network based
Synthesis for Supervised Medical Image Segmentation, author=Neff, Thomas and
Payer, Christian and Štern, Darko and Urschler, Martin, booktitle=OAGM & ARW
Joint Workshop 2017 on “Vision, Automation & Robotics”, year=2017,
organization=Verlag der Technischen Universität Graz

@articlefrid2018gan, title=GAN-based Synthetic Medical Image Augmentation for
increased CNN Performance in Liver Lesion Classification, author=Frid-Adar,
Maayan and Diamant, Idit and Klang, Eyal and Amitai, Michal and Goldberger,
Jacob and Greenspan, Hayit, journal=arXiv preprint arXiv:1803.01229, year=2018

@articleschawinski2017generative, title=Generative adversarial networks
recover features in astrophysical images of galaxies beyond the deconvolution
limit, author=Schawinski, Kevin and Zhang, Ce and Zhang, Hantian and Fowler,
Lucas and Santhanam, Gokula Krishnan, journal=Monthly Notices of the Royal
Astronomical Society: Letters, volume=467, number=1, pages=L110–L114,
year=2017, publisher=Oxford University Press

@articlepoplin2018prediction, title=Prediction of cardiovascular risk factors
from retinal fundus photographs via deep learning, author=Poplin, Ryan and
Varadarajan, Avinash V and Blumer, Katy and Liu, Yun and McConnell, Michael V
and Corrado, Greg S and Peng, Lily and Webster, Dale R, journal=Nature
Biomedical Engineering, volume=2, number=3, pages=158, year=2018,
publisher=Nature Publishing Group @articleseoud2016red, title=Red lesion
detection using dynamic shape features for diabetic retinopathy screening,
author=Seoud, Lama and Hurtut, Thomas and Chelbi, Jihed and Cheriet, Farida
and Langlois, JM Pierre, journal=IEEE transactions on medical imaging,
volume=35, number=4, pages=1116–1126, year=2016, publisher=IEEE

@articleting2017development, title=Development and validation of a deep
learning system for diabetic retinopathy and related eye diseases using
retinal images from multiethnic populations with diabetes, author=Ting, Daniel
Shu Wei and Cheung, Carol Yim-Lui and Lim, Gilbert and Tan, Gavin Siew Wei and
Quang, Nguyen D and Gan, Alfred and Hamzah, Haslina and Garcia-Franco, Renata
and San Yeo, Ian Yew and Lee, Shu Yen and others, journal=Jama, volume=318,
number=22, pages=2211–2223, year=2017, publisher=American Medical Association

@articlevan2003photography, title=Photography or ophthalmoscopy for detection
of diabetic retinopathy?, author=van Leiden, Hendrik A and Moll, Annette C and
Dekker, Jacqueline M and Abramoff, Michael D and Polak, Bettine CP,
journal=Diabetes care, volume=26, number=4, pages=1318–1319, year=2003,
publisher=Am Diabetes Assoc

@inproceedingslee1994parallel, title=Parallel grading of venous beading on
transputer, author=Lee, Tien-You and Cheng, HD, booktitle=Proceedings of 1994
20th Annual Northeast Bioengineering Conference, pages=54–58, year=1994,
organization=IEEE

@articleearly1987treatment, title=Treatment techniques and clinical guidelines
for photocoagulation of diabetic macular edema: Early Treatment Diabetic
Retinopathy Study report number 2, author=Early Treatment Diabetic Retinopathy
Study Research Group and others, journal=Ophthalmology, volume=94, number=7,
pages=761–774, year=1987, publisher=Elsevier

@articlewong2016artificial, title=Artificial intelligence with deep learning
technology looks into diabetic retinopathy screening, author=Wong, Tien Yin
and Bressler, Neil M, journal=Jama, volume=316, number=22, pages=2366–2367,
year=2016, publisher=American Medical Association

@articlelawrence2004accuracy, title=The accuracy of digital-video retinal
imaging to screen for diabetic retinopathy: an analysis of two digital-video
retinal imaging systems using standard stereoscopic seven-field photography
and dilated clinical examination as reference standards, author=Lawrence, Mary
Gilbert, journal=Transactions of the American Ophthalmological Society,
volume=102, pages=321, year=2004, publisher=American Ophthalmological Society

@articlemassin2003evaluation, title=Evaluation of a new non-mydriatic digital
camera for detection of diabetic retinopathy, author=Massin, P and Erginay, A
and Ben Mehidi, A and Vicaut, E and Quentel, G and Victor, Z and Marre, M and
Guillausseau, PJ and Gaudric, A, journal=Diabetic medicine, volume=20,
number=8, pages=635–641, year=2003, publisher=Wiley Online Library

@articleroy2020incremental, title=Incremental dilations using CNN for brain
tumor classification, author=Roy, Sanjiban Sekhar and Rodrigues, Nishant and
Taguchi, Yh, journal=Applied Sciences, volume=10, number=14, pages=4915,
year=2020, publisher=Multidisciplinary Digital Publishing Institute

@articleyaqoob2021resnet, title=ResNet Based Deep Features and Random Forest
Classifier for Diabetic Retinopathy Detection, author=Yaqoob, Muhammad Kashif
and Ali, Syed Farooq and Bilal, Muhammad and Hanif, Muhammad Shehzad and Al-
Saggaf, Ubaid M, journal=Sensors, volume=21, number=11, pages=3883, year=2021,
publisher=Multidisciplinary Digital Publishing Institute

@articlewan2018deep, title=Deep convolutional neural networks for diabetic
retinopathy detection by image classification, author=Wan, Shaohua and Liang,
Yan and Zhang, Yin, journal=Computers & Electrical Engineering, volume=72,
pages=274–282, year=2018, publisher=Elsevier

@inproceedingsyu2017dilated, title=Dilated residual networks, author=Yu,
Fisher and Koltun, Vladlen and Funkhouser, Thomas, booktitle=Proceedings of
the IEEE conference on computer vision and pattern recognition, pages=472–480,
year=2017

@articleszabo2015telemedical, title=Telemedical diabetic retinopathy screening
in Hungary: a pilot programme, author=Szabó, Dorottya and Fiedler, Orsolya and
Somogyi, Anikó and Somfai, Gábor Márk and Bíró, Zsolt and Ölvedy, Veronika and
Hargitai, Zsófia and Németh, János, journal=Journal of telemedicine and
telecare, volume=21, number=3, pages=167–173, year=2015, publisher=SAGE
Publications Sage UK: London, England

@articleabdellaoui2016screening, title=Screening for diabetic retinopathy by
non-mydriatic retinal camera in the region of Fez, author=Abdellaoui, M and
Marrakchi, M and Benatiya, IA and Tahri, H, journal=Journal francais
d’ophtalmologie, volume=39, number=1, pages=48–54, year=2016

@inproceedingsvedaldi2015matconvnet, title=Matconvnet: Convolutional neural
networks for matlab, author=Vedaldi, Andrea and Lenc, Karel,
booktitle=Proceedings of the 23rd ACM international conference on Multimedia,
pages=689–692, year=2015

@articleli2019diagnostic, title=Diagnostic assessment of deep learning
algorithms for diabetic retinopathy screening, author=Li, Tao and Gao, Yingqi
and Wang, Kai and Guo, Song and Liu, Hanruo and Kang, Hong,
journal=Information Sciences, volume=501, pages=511–522, year=2019,
publisher=Elsevier

@articlebezdek1984fcm, title=FCM: The fuzzy c-means clustering algorithm,
author=Bezdek, James C and Ehrlich, Robert and Full, William,
journal=Computers & Geosciences, volume=10, number=2-3, pages=191–203,
year=1984, publisher=Pergamon

@articleAzzopardi, author = Azzopardi, George and Strisciuglio, Nicola and
Vento, Mario and Petkov, Nicolai, year = 2015, month = 01, pages = 46-57,
title = Trainable COSFIRE filters for vessel delineation with application to
retinal images, volume = 19, journal = Medical Image Analysis, doi =
10.1016/j.media.2014.08.002

@articlereza2004realization, title=Realization of the contrast limited
adaptive histogram equalization (CLAHE) for real-time image enhancement,
author=Reza, Ali M, journal=Journal of VLSI signal processing systems for
signal, image and video technology, volume=38, number=1, pages=35–44,
year=2004, publisher=Springer

@bookgonzalez2004digital, title=Digital image processing using MATLAB,
author=Gonzalez, Rafael C and Woods, Richard E and Eddins, Steven L,
year=2004, publisher=Pearson Education India

@articlesiu1998effectiveness, title=Effectiveness of non-mydriatic retinal
photography and direct ophthalmoscopy in detecting diabetic retinopathy,
author=Siu, SC and Ko, TC and Wong, KW and Chan, WN and others, journal=Hong
Kong Medical Journal, pages=367–370, year=1998, publisher=Citeseer

@articlechow2006comparison, title=Comparison of nonmydriatic digital retinal
imaging versus dilated ophthalmic examination for nondiabetic eye disease in
persons with diabetes, author=Chow, Sing-Pey and Aiello, Lloyd M and
Cavallerano, Jerry D and Katalinic, Paula and Hock, Kristen and Tolson, Ann
and Kirby, Rita and Bursell, Sven-Erik and Aiello, Lloyd Paul,
journal=Ophthalmology, volume=113, number=5, pages=833–840, year=2006,
publisher=Elsevier

@articlewong2016artificial, title=Artificial intelligence with deep learning
technology looks into diabetic retinopathy screening, author=Wong, Tien Yin
and Bressler, Neil M, journal=Jama, volume=316, number=22, pages=2366–2367,
year=2016, publisher=American Medical Association

@articlesevastopolsky2017optic, title=Optic disc and cup segmentation methods
for glaucoma detection with modification of U-Net convolutional neural
network, author=Sevastopolsky, Artem, journal=Pattern Recognition and Image
Analysis, volume=27, number=3, pages=618–624, year=2017, publisher=Springer

@articleguo2016optic, title=Optic cup segmentation using large pixel patch
based CNNs, author=Guo, Yundi and Zou, Beiji and Chen, Zailiang and He, Qi and
Liu, Qing and Zhao, Rongchang, year=2016, publisher=University of Iowa

@miscoO, title = o O CNN solution, howpublished =
https://www.kaggle.com/c/diabetic-retinopathydetection/discussion/15617, note
= Accessed: 2017-01-16

@miscseed, title = SEED-DB, howpublished = https://www.seri.com.sg/key-
programmes/singapore-epidemiology-of-eye-diseases-seed/, note = Assessed on
2018-08-08

@articlefraz2012ensemble, title=An ensemble classification-based approach
applied to retinal blood vessel segmentation, author=Fraz, Muhammad Moazam and
Remagnino, Paolo and Hoppe, Andreas and Uyyanonvara, Bunyarit and Rudnicka,
Alicja R and Owen, Christopher G and Barman, Sarah A, journal=IEEE
Transactions on Biomedical Engineering, volume=59, number=9, pages=2538–2548,
year=2012, publisher=IEEE

@articlealmazroa2015optic, title=Optic disc and optic cup segmentation
methodologies for glaucoma image detection: a survey, author=Almazroa, Ahmed
and Burman, Ritambhar and Raahemifar, Kaamran and Lakshminarayanan, Vasudevan,
journal=Journal of ophthalmology, volume=2015, year=2015, publisher=Hindawi
@articleaquino2010detecting, title=Detecting the optic disc boundary in
digital fundus images using morphological, edge detection, and feature
extraction techniques, author=Aquino, Arturo and Gegúndez-Arias, Manuel Emilio
and Marín, Diego, journal=IEEE transactions on medical imaging, volume=29,
number=11, pages=1860–1869, year=2010, publisher=IEEE

@articletjandrasa2012optic, title=Optic nerve head segmentation using hough
transform and active contours, author=Tjandrasa, Handayani and Wijayanti, Ari
and Suciati, Nanik, journal=Indonesian Journal of Electrical Engineering and
Computer Science, volume=10, number=3, pages=531–536, year=2012
@inproceedingsmaninis2016deep, title=Deep retinal image understanding,
author=Maninis, Kevis-Kokitsi and Pont-Tuset, Jordi and Arbeláez, Pablo and
Van Gool, Luc, booktitle=International Conference on Medical Image Computing
and Computer-Assisted Intervention, pages=140–148, year=2016,
organization=Springer

@articlezilly2017glaucoma, title=Glaucoma detection using entropy sampling and
ensemble learning for automatic optic cup and disc segmentation, author=Zilly,
Julian and Buhmann, Joachim M and Mahapatra, Dwarikanath, journal=Computerized
Medical Imaging and Graphics, volume=55, pages=28–41, year=2017,
publisher=Elsevier

@inproceedingssharma2018modular, title=Modular Neural Network for Detection of
Diabetic Retinopathy in Retinal Images, author=Sharma, Manish and Sharma,
Praveen and Saini, Ashwini and Sharma, Kirti, booktitle=Proceedings of First
International Conference on Smart System, Innovations and Computing,
pages=363–370, year=2018, organization=Springer

@articleoh2002class, title=A class-modular feedforward neural network for
handwriting recognition, author=Oh, Il-Seok and Suen, Ching Y, journal=pattern
recognition, volume=35, number=1, pages=229–244, year=2002, publisher=Elsevier

@inproceedingskrahenbuhl2014geodesic, title=Geodesic object proposals,
author=Krähenbühl, Philipp and Koltun, Vladlen, booktitle=European conference
on computer vision, pages=725–739, year=2014, organization=Springer

@articlejiang2019automatic, title=Automatic Retinal Blood Vessel Segmentation
Based on Fully Convolutional Neural Networks, author=Jiang, Yun and Zhang, Hai
and Tan, Ning and Chen, Li, journal=Symmetry, volume=11, number=9, pages=1112,
year=2019, publisher=Multidisciplinary Digital Publishing Institute

@articletang2020multi, title=Multi-scale channel importance sorting and
spatial attention mechanism for retinal vessels segmentation, author=Tang,
Xianlun and Zhong, Bing and Peng, Jiangping and Hao, Bohui and Li, Jie,
journal=Applied Soft Computing, pages=106353, year=2020, publisher=Elsevier

@inproceedingsarbelaez2014multiscale, title=Multiscale combinatorial grouping,
author=Arbeláez, Pablo and Pont-Tuset, Jordi and Barron, Jonathan T and
Marques, Ferran and Malik, Jitendra, booktitle=Proceedings of the IEEE
conference on computer vision and pattern recognition, pages=328–335,
year=2014

@inproceedingsroy2015dasa, title=Dasa: Domain adaptation in stacked
autoencoders using systematic dropout, author=Roy, Abhijit Guha and Sheet,
Debdoot, booktitle=Pattern Recognition (ACPR), 2015 3rd IAPR Asian Conference
on, pages=735–739, year=2015, organization=IEEE

@articletang2017selective, title=Selective search and intensity context based
retina vessel image segmentation, author=Tang, Zhaohui and Zhang, Jin and Gui,
Weihua, journal=Journal of medical systems, volume=41, number=3, pages=47,
year=2017, publisher=Springer

@articlealmotiri2018retinal, title=Retinal Vessels Segmentation Techniques and
Algorithms: A Survey, author=Almotiri, Jasem and Elleithy, Khaled and
Elleithy, Abdelrahman, journal=Applied Sciences, volume=8, number=2,
pages=155, year=2018, publisher=Multidisciplinary Digital Publishing Institute

@articlevillalobos2010fast, title=A fast, efficient and automated method to
extract vessels from fundus images, author=Villalobos-Castaldi, Fabiola M and
Felipe-Riverón, Edgardo M and Sánchez-Fernández, Luis P, journal=Journal of
Visualization, volume=13, number=3, pages=263–270, year=2010,
publisher=Springer

@miscaleqt, title=Prevalence and causes of blindness and diabetic retinopathy
in Southern Saudi Arabia, author=Hajar, Saad and Al Hazmi, Ali and Wasli,
Mustafa and Mousa, Ahmed and Rabiu, Mansour, journal=Saudi medical journal,
volume=36, number=4, pages=449, year=2015, publisher=Saudi Medical Journal

@miscokaz, title=Rapid assessment of avoidable blindness and diabetic
retinopathy in Taif, Saudi Arabia, author=Al Ghamdi, Abdul Hamid and Rabiu,
Mansur and Hajar, Saad and Yorston, David and Kuper, Hannah and Polack, Sarah,
journal=British journal of ophthalmology, volume=96, number=9,
pages=1168–1172, year=2012, publisher=BMJ Publishing Group Ltd

@inproceedingsperdomo2017convolutional, title=Convolutional network to detect
exudates in eye fundus images of diabetic subjects, author=Perdomo, Oscar and
Arevalo, John and González, Fabio A, booktitle=12th International Symposium on
Medical Information Processing and Analysis, volume=10160, pages=101600T,
year=2017, organization=International Society for Optics and Photonics

@articlehaloi2015improved, title=Improved microaneurysm detection using deep
neural networks, author=Haloi, Mrinal, journal=arXiv preprint
arXiv:1505.04424, year=2015

@inproceedingszhang2018automatic, title=Automatic localization and
segmentation of optical disk based on faster R-CNN and level set in fundus
image, author=Zhang, Defeng and Zhu, Weifang and Zhao, Heming and Shi, Fei and
Chen, Xinjian, booktitle=Medical Imaging 2018: Image Processing, volume=10574,
pages=105741U, year=2018, organization=International Society for Optics and
Photonics

@articlecondurache2012segmentation, title=Segmentation of retinal vessels with
a hysteresis binary-classification paradigm, author=Condurache, Alexandru Paul
and Mertins, Alfred, journal=Computerized Medical Imaging and Graphics,
volume=36, number=4, pages=325–335, year=2012, publisher=Elsevier

@articlesrinidhi2017recent, title=Recent advancements in retinal vessel
segmentation, author=Srinidhi, Chetan L and Aparna, P and Rajan, Jeny,
journal=Journal of medical systems, volume=41, number=4, pages=70, year=2017,
publisher=Springer

@articleaquino2010detecting, title=Detecting the optic disc boundary in
digital fundus images using morphological, edge detection, and feature
extraction techniques, author=Aquino, Arturo and Gegúndez-Arias, Manuel Emilio
and Marín, Diego, journal=IEEE transactions on medical imaging, volume=29,
number=11, pages=1860–1869, year=2010, publisher=IEEE

@inproceedingszhang2012optic, title=Optic disc localization by projection with
vessel distribution and appearance characteristics, author=Zhang, Dongbo and
Yi, Yao and Shang, Xingyu and Peng, Yinghui, booktitle=Pattern Recognition
(ICPR), 2012 21st International Conference on, pages=3176–3179, year=2012,
organization=IEEE

@inproceedingssinha2012optic, title=Optic disk localization using L 1
minimization, author=Sinha, Neelam and Babu, R Venkatesh, booktitle=Image
Processing (ICIP), 2012 19th IEEE International Conference on,
pages=2829–2832, year=2012, organization=IEEE

@articleliskowski2016segmenting, title=Segmenting retinal blood vessels with
deep neural networks, author=Liskowski, Paweł and Krawiec, Krzysztof,
journal=IEEE transactions on medical imaging, volume=35, number=11,
pages=2369–2380, year=2016, publisher=IEEE

@incollectionxu2017optic, title=Optic Disc Detection via Deep Learning in
Fundus Images, author=Xu, Peiyuan and Wan, Cheng and Cheng, Jun and Niu, Di
and Liu, Jiang, booktitle=Fetal, Infant and Ophthalmic Medical Image Analysis,
pages=134–141, year=2017, publisher=Springer

@articlewu2017automatic, title=Automatic detection of microaneurysms in
retinal fundus images, author=Wu, Bo and Zhu, Weifang and Shi, Fei and Zhu,
Shuxia and Chen, Xinjian, journal=Computerized Medical Imaging and Graphics,
volume=55, pages=106–112, year=2017, publisher=Elsevier

@articlesabeenian2017automated, title=An Automated Detection of Microaneursym
to facilitate better Diagnosis of Diabetic Retinopathy, author=Sabeenian, RS
and Surendar, A and others, journal=Biosciences Biotechnology Research Asia,
volume=10, number=1, pages=483–488, year=2017

@articlelong2020microaneurysms, title=Microaneurysms detection in color fundus
images using machine learning based on directional local contrast,
author=Long, Shengchun and Chen, Jiali and Hu, Ante and Liu, Haipeng and Chen,
Zhiqing and Zheng, Dingchang, journal=Biomedical engineering online,
volume=19, pages=1–23, year=2020, publisher=Springer

@articleeftekhari2019microaneurysm, title=Microaneurysm detection in fundus
images using a two-step convolutional neural network, author=Eftekhari,
Noushin and Pourreza, Hamid-Reza and Masoudi, Mojtaba and Ghiasi-Shirazi,
Kamaledin and Saeedi, Ehsan, journal=Biomedical engineering online, volume=18,
number=1, pages=1–16, year=2019, publisher=Springer

@articlezhang2019detection, title=Detection of Microaneurysms in Fundus Images
Based on an Attention Mechanism, author=Zhang, Lizong and Feng, Shuxin and
Duan, Guiduo and Li, Ying and Liu, Guisong, journal=Genes, volume=10,
number=10, pages=817, year=2019, publisher=Multidisciplinary Digital
Publishing Institute

@inproceedingssingh2018analysis, title=An analysis of scale invariance in
object detection snip, author=Singh, Bharat and Davis, Larry S,
booktitle=Proceedings of the IEEE conference on computer vision and pattern
recognition, pages=3578–3587, year=2018

@articleoke2016use, title=The use of statistical methodology to determine the
accuracy of grading within a diabetic retinopathy screening programme,
author=Oke, JL and Stratton, IM and Aldington, SJ and Stevens, RJ and Scanlon,
Peter H, journal=Diabetic Medicine, volume=33, number=7, pages=896–903,
year=2016, publisher=Wiley Online Library @articleli2017scale, title=Scale-
aware fast R-CNN for pedestrian detection, author=Li, Jianan and Liang,
Xiaodan and Shen, ShengMei and Xu, Tingfa and Feng, Jiashi and Yan, Shuicheng,
journal=IEEE transactions on Multimedia, volume=20, number=4, pages=985–996,
year=2017, publisher=IEEE

@articlewilkinson2003proposed, title=Proposed international clinical diabetic
retinopathy and diabetic macular edema disease severity scales,
author=Wilkinson, CP and Ferris III, Frederick L and Klein, Ronald E and Lee,
Paul P and Agardh, Carl David and Davis, Matthew and Dills, Diana and Kampik,
Anselm and Pararajasegaram, R and Verdaguer, Juan T and others,
journal=Ophthalmology, volume=110, number=9, pages=1677–1682, year=2003,
publisher=Elsevier

@articlemarin2018exudate, title=An exudate detection method for diagnosis risk
of diabetic macular edema in retinal images using feature-based and supervised
classification, author=Marin, D and Gegundez-Arias, ME and Ponte, B and
Alvarez, F and Garrido, J and Ortega, C and Vasallo, MJ and Bravo, JM,
journal=Medical & biological engineering & computing, pages=1–12, year=2018,
publisher=Springer

@inproceedingsdasgupta2017fully, title=A fully convolutional neural network
based structured prediction approach towards the retinal vessel segmentation,
author=Dasgupta, Avijit and Singh, Sonam, booktitle=Biomedical Imaging (ISBI
2017), 2017 IEEE 14th International Symposium on, pages=248–251, year=2017,
organization=IEEE

@inproceedingshuang2017densely, title=Densely connected convolutional
networks, author=Huang, Gao and Liu, Zhuang and Van Der Maaten, Laurens and
Weinberger, Kilian Q, booktitle=Proceedings of the IEEE conference on computer
vision and pattern recognition, pages=4700–4708, year=2017

@articlehuang2018automatic, title=Automatic detection of neovascularization in
retinal images using extreme learning machine, author=Huang, He and Ma, He and
van Triest, Han JW and Wei, Yinghua and Qian, Wei, journal=Neurocomputing,
volume=277, pages=218–227, year=2018, publisher=Elsevier

@articlefleming2007automated, title=Automated detection of exudates for
diabetic retinopathy screening, author=Fleming, Alan D and Philip, Sam and
Goatman, Keith A and Williams, Graeme J and Olson, John A and Sharp, Peter F,
journal=Physics in Medicine & Biology, volume=52, number=24, pages=7385,
year=2007, publisher=IOP Publishing

@articlefleming2006automatic, title=Automatic detection of retinal anatomy to
assist diabetic retinopathy screening, author=Fleming, Alan D and Goatman,
Keith A and Philip, Sam and Olson, John A and Sharp, Peter F, journal=Physics
in Medicine & Biology, volume=52, number=2, pages=331, year=2006,
publisher=IOP Publishing

@articlefleming2010role, title=The role of haemorrhage and exudate detection
in automated grading of diabetic retinopathy, author=Fleming, Alan D and
Goatman, Keith A and Philip, Sam and Williams, Graeme J and Prescott, Gordon J
and Scotland, Graham S and McNamee, Paul and Leese, Graham P and Wykes,
William N and Sharp, Peter F and others, journal=British Journal of
Ophthalmology, volume=94, number=6, pages=706–711, year=2010, publisher=BMJ
Publishing Group Ltd

@articlefaust2012algorithms, title=Algorithms for the automated detection of
diabetic retinopathy using digital fundus images: a review, author=Faust,
Oliver and Acharya, Rajendra and Ng, Eddie Yin-Kwee and Ng, Kwan-Hoong and
Suri, Jasjit S, journal=Journal of medical systems, volume=36, number=1,
pages=145–157, year=2012, publisher=Springer

@articleacharya2009computer, title=Computer-based detection of diabetes
retinopathy stages using digital fundus images, author=Acharya, Udyavara R and
Lim, Choo M and Ng, E Yin Kwee and Chee, Caroline and Tamura, Toshiyo,
journal=Proceedings of the institution of mechanical engineers, part H:
journal of engineering in medicine, volume=223, number=5, pages=545–553,
year=2009, publisher=SAGE Publications Sage UK: London, England

@articleyun2008identification, title=Identification of different stages of
diabetic retinopathy using retinal optical images, author=Yun, Wong Li and
Acharya, U Rajendra and Venkatesh, Yedatore V and Chee, Caroline and Min, Lim
Choo and Ng, E Yin Kwee, journal=Information sciences, volume=178, number=1,
pages=106–121, year=2008, publisher=Elsevier

@miscwebref, title = Diabetic Retinopathy., howpublished =
http://www.icoph.org/standards/pdrdetail.html, note = Accessed: 2009-1-17

@miscwebref2, title = nternational Council of Ophthalmology. International
standards: international clinical diabetic retinopathy disease severity scale,
detailed table., howpublished = http://www.hoptechno.com/book45.htm, note =
Accessed: 2009-1-17

@articleciulla2003diabetic, title=Diabetic retinopathy and diabetic macular
edema: pathophysiology, screening, and novel therapies, author=Ciulla, Thomas
A and Amador, Armando G and Zinman, Bernard, journal=Diabetes care, volume=26,
number=9, pages=2653–2664, year=2003, publisher=Am Diabetes Assoc

@articlelahmiri2014automated, title=Automated detection of circinate exudates
in retina digital images using empirical mode decomposition and the entropy
and uniformity of the intrinsic mode functions, author=Lahmiri, Salim and
Boukadoum, Mounir, journal=Biomedical Engineering/Biomedizinische Technik,
volume=59, number=4, pages=357–366, year=2014, publisher=De Gruyter

@articlenayak2009automatic, title=Automatic identification of diabetic
maculopathy stages using fundus images, author=Nayak, Jagadish and Bhat, P
Subbanna and Acharya, UR, journal=Journal of medical engineering & technology,
volume=33, number=2, pages=119–129, year=2009, publisher=Taylor & Francis

@articlekaur2018generalized, title=A generalized method for the segmentation
of exudates from pathological retinal fundus images, author=Kaur, Jaskirat and
Mittal, Deepti, journal=Biocybernetics and Biomedical Engineering, volume=38,
number=1, pages=27–53, year=2018, publisher=Elsevier

@articlejoshi2018review, title=A review on exudates detection methods for
diabetic retinopathy, author=Joshi, Shilpa and Karule, PT, journal=Biomedicine
& Pharmacotherapy, volume=97, pages=1454–1460, year=2018, publisher=Elsevier

@articlezou2004statistical, title=Statistical validation of image segmentation
quality based on a spatial overlap index1: scientific reports, author=Zou,
Kelly H and Warfield, Simon K and Bharatha, Aditya and Tempany, Clare MC and
Kaus, Michael R and Haker, Steven J and Wells, William M and Jolesz, Ferenc A
and Kikinis, Ron, journal=Academic radiology, volume=11, number=2,
pages=178–189, year=2004, publisher=Elsevier

@articlezhang2015segmentation, title=Segmentation quality evaluation using
region-based precision and recall measures for remote sensing images,
author=Zhang, Xueliang and Feng, Xuezhi and Xiao, Pengfeng and He, Guangjun
and Zhu, Liujun, journal=ISPRS Journal of Photogrammetry and Remote Sensing,
volume=102, pages=73–84, year=2015, publisher=Elsevier

@incollectionmitchell2004role, title=The role of unlabeled data in supervised
learning, author=Mitchell, Tom M, booktitle=Language, Knowledge, and
Representation, pages=103–111, year=2004, publisher=Springer

@articlealtman1994diagnostic, title=Diagnostic tests. 1: Sensitivity and
specificity., author=Altman, Douglas G and Bland, J Martin, journal=BMJ:
British Medical Journal, volume=308, number=6943, pages=1552, year=1994,
publisher=BMJ Publishing Group @articlethakur2018survey, title=Survey on
segmentation and classification approaches of optic cup and optic disc for
diagnosis of glaucoma, author=Thakur, Niharika and Juneja, Mamta,
journal=Biomedical Signal Processing and Control, volume=42, pages=162–189,
year=2018, publisher=Elsevier

@articlesopharak2008automatic, title=Automatic detection of diabetic
retinopathy exudates from non-dilated retinal images using mathematical
morphology methods, author=Sopharak, Akara and Uyyanonvara, Bunyarit and
Barman, Sarah and Williamson, Thomas H, journal=Computerized medical imaging
and graphics, volume=32, number=8, pages=720–727, year=2008,
publisher=Elsevier

@inproceedingsmassey2009robust, title=A robust lesion boundary segmentation
algorithm using level set methods, author=Massey, EM and Hunter, Andrew and
Lowell, James and Steel, DH, booktitle=World Congress on Medical Physics and
Biomedical Engineering, September 7-12, 2009, Munich, Germany, pages=304–307,
year=2009, organization=Springer

@articlereza2009automatic, title=Automatic tracing of optic disc and exudates
from color fundus images using fixed and variable thresholds, author=Reza,
Ahmed Wasif and Eswaran, Chantra and Hati, Subhas, journal=Journal of medical
systems, volume=33, number=1, pages=73, year=2009, publisher=Springer

@articleusher2004automated, title=Automated detection of diabetic retinopathy
in digital retinal images: a tool for diabetic retinopathy screening,
author=Usher, Dumskyj and Dumskyj, M and Himaga, Mitsutoshi and Williamson,
Tom H and Nussey, Sl and Boyce, J, journal=Diabetic Medicine, volume=21,
number=1, pages=84–90, year=2004, publisher=Wiley Online Library

@articleganesan2014computer, title=Computer-aided diabetic retinopathy
detection using trace transforms on digital fundus images, author=Ganesan,
Karthikeyan and Martis, Roshan Joy and Acharya, U Rajendra and Chua, Chua
Kuang and Min, Lim Choo and Ng, EYK and Laude, Augustinus, journal=Medical &
biological engineering & computing, volume=52, number=8, pages=663–672,
year=2014, publisher=Springer

@articlesanchez2009retinal, title=Retinal image analysis based on mixture
models to detect hard exudates, author=Sánchez, Clara I and García, María and
Mayo, Agustín and López, María I and Hornero, Roberto, journal=Medical Image
Analysis, volume=13, number=4, pages=650–658, year=2009, publisher=Elsevier

@articleosareh2003automated, title=Automated identification of diabetic
retinal exudates in digital colour images, author=Osareh, Alireza and
Mirmehdi, Majid and Thomas, Bari and Markham, Richard, journal=British Journal
of Ophthalmology, volume=87, number=10, pages=1220–1223, year=2003,
publisher=BMJ Publishing Group Ltd @articlegarcia2009neural, title=Neural
network based detection of hard exudates in retinal images, author=García,
María and Sánchez, Clara I and López, María I and Abásolo, Daniel and Hornero,
Roberto, journal=Computer Methods and programs in biomedicine, volume=93,
number=1, pages=9–19, year=2009, publisher=Elsevier

@articlequreshi2012combining, title=Combining algorithms for automatic
detection of optic disc and macula in fundus images, author=Qureshi, Rashid
Jalal and Kovacs, Laszlo and Harangi, Balazs and Nagy, Brigitta and Peto,
Tunde and Hajdu, Andras, journal=Computer Vision and Image Understanding,
volume=116, number=1, pages=138–145, year=2012, publisher=Elsevier

@inproceedingsgiancardo2011microaneurysm, title=Microaneurysm detection with
radon transform-based classification on retina images, author=Giancardo, Luca
and Meriaudeau, Fabrice and Karnowski, Thomas P and Li, Yaqin and Tobin, KW
and Chaum, Edward, booktitle=Engineering in Medicine and Biology Society,
EMBC, 2011 Annual International Conference of the IEEE, pages=5939–5942,
year=2011, organization=IEEE

@articlegiancardo2012exudate, title=Exudate-based diabetic macular edema
detection in fundus images using publicly available datasets,
author=Giancardo, Luca and Meriaudeau, Fabrice and Karnowski, Thomas P and Li,
Yaqin and Garg, Seema and Tobin, Kenneth W and Chaum, Edward, journal=Medical
image analysis, volume=16, number=1, pages=216–226, year=2012,
publisher=Elsevier

@articlequellec2012multiple, title=A multiple-instance learning framework for
diabetic retinopathy screening, author=Quellec, Gwénolé and Lamard, Mathieu
and Abràmoff, Michael D and Decencière, Etienne and Lay, Bruno and Erginay,
Ali and Cochener, Béatrice and Cazuguel, Guy, journal=Medical image analysis,
volume=16, number=6, pages=1228–1240, year=2012, publisher=Elsevier

@articlezhang2012sparse, title=Sparse representation classifier for
microaneurysm detection and retinal blood vessel extraction, author=Zhang, Bob
and Karray, Fakhri and Li, Qin and Zhang, Lei, journal=Information Sciences,
volume=200, pages=78–90, year=2012, publisher=Elsevier

@articlesanchez2008novel, title=A novel automatic image processing algorithm
for detection of hard exudates based on retinal image analysis,
author=Sánchez, Clara I and Hornero, Roberto and López, María I and Aboy,
Mateo and Poza, Jesús and Abásolo, Daniel, journal=Medical Engineering and
Physics, volume=30, number=3, pages=350–357, year=2008, publisher=Elsevier

@articleakram2013identification, title=Identification and classification of
microaneurysms for early detection of diabetic retinopathy, author=Akram, M
Usman and Khalid, Shehzad and Khan, Shoab A, journal=Pattern Recognition,
volume=46, number=1, pages=107–116, year=2013, publisher=Elsevier

@articlekose2012simple, title=Simple methods for segmentation and measurement
of diabetic retinopathy lesions in retinal fundus images, author=Köse, Cemal
and ŞEvik, UğUr and İKibaş, Cevat and Erdöl, Hidayet, journal=Computer methods
and programs in biomedicine, volume=107, number=2, pages=274–293, year=2012,
publisher=Elsevier

@articlekose2012simple, title=Simple methods for segmentation and measurement
of diabetic retinopathy lesions in retinal fundus images, author=Köse, Cemal
and ŞEvik, UğUr and İKibaş, Cevat and Erdöl, Hidayet, journal=Computer methods
and programs in biomedicine, volume=107, number=2, pages=274–293, year=2012,
publisher=Elsevier

@articleaptel2008screening, title=Screening of diabetic retinopathy: effect of
field number and mydriasis on sensitivity and specificity of digital fundus
photography, author=Aptel, F and Denis, P and Rouberol, F and Thivolet, C,
journal=Diabetes & metabolism, volume=34, number=3, pages=290–293, year=2008,
publisher=Elsevier

@articleabramoff2010automated, title=Automated early detection of diabetic
retinopathy, author=Abràmoff, Michael D and Reinhardt, Joseph M and Russell,
Stephen R and Folk, James C and Mahajan, Vinit B and Niemeijer, Meindert and
Quellec, Gwénolé, journal=Ophthalmology, volume=117, number=6,
pages=1147–1154, year=2010, publisher=Elsevier

@inproceedingsgiancardo2013validation, title=Validation of microaneurysm-based
diabetic retinopathy screening across retina fundus datasets,
author=Giancardo, Luca and Karnowski, Thomas P and Tobin, Kenneth W and
Meriaudeau, Fabrice and Chaum, Edward, booktitle=Computer-Based Medical
Systems (CBMS), 2013 IEEE 26th International Symposium on, pages=125–130,
year=2013, organization=IEEE

@articlezhang2010detection, title=Detection of microaneurysms using multi-
scale correlation coefficients, author=Zhang, Bob and Wu, Xiangqian and You,
Jane and Li, Qin and Karray, Fakhri, journal=Pattern Recognition, volume=43,
number=6, pages=2237–2248, year=2010, publisher=Elsevier

@articlejavidi2017vessel, title=Vessel segmentation and microaneurysm
detection using discriminative dictionary learning and sparse representation,
author=Javidi, Malihe and Pourreza, Hamid-Reza and Harati, Ahad,
journal=Computer methods and programs in biomedicine, volume=139,
pages=93–108, year=2017, publisher=Elsevier

@articleperdomo2016novel, title=A novel machine learning model based on
exudate localization to detect diabetic macular edema, author=Perdomo, Oscar
and Otalora, Sebastian and Rodríguez, Francisco and Arevalo, John and
González, Fabio A, year=2016, publisher=University of Iowa

@articleabramoff2016improved, title=Improved automated detection of diabetic
retinopathy on a publicly available dataset through integration of deep
learning, author=Abràmoff, Michael David and Lou, Yiyue and Erginay, Ali and
Clarida, Warren and Amelon, Ryan and Folk, James C and Niemeijer, Meindert,
journal=Investigative ophthalmology & visual science, volume=57, number=13,
pages=5200–5206, year=2016, publisher=The Association for Research in Vision
and Ophthalmology

@inproceedingskarnowski2008retina, title=Retina lesion and microaneurysm
segmentation using morphological reconstruction methods with ground-truth
data, author=Karnowski, Thomas P and Govindasamy, V Priya and Tobin, Kenneth W
and Chaum, Edward and Abramoff, MD, booktitle=Engineering in Medicine and
Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the
IEEE, pages=5433–5436, year=2008, organization=IEEE

@articlesevastopolsky2017optic, title=Optic disc and cup segmentation methods
for glaucoma detection with modification of U-Net convolutional neural
network, author=Sevastopolsky, Artem, journal=Pattern Recognition and Image
Analysis, volume=27, number=3, pages=618–624, year=2017, publisher=Springer

@articlesbeh2001new, title=A new approach of geodesic reconstruction for
drusen segmentation in eye fundus images, author=Sbeh, Z Ben and Cohen,
Laurent D and Mimoun, Gérard and Coscas, Gabriel, journal=IEEE Transactions on
medical imaging, volume=20, number=12, pages=1321–1333, year=2001,
publisher=IEEE

@inproceedingstobin2006characterization, title=Characterization of the optic
disc in retinal imagery using a probabilistic approach, author=Tobin, Kenneth
W and Chaum, Edward and Govindasamy, V Priya and Karnowski, Thomas P and
Sezer, Omer, booktitle=Medical Imaging 2006: Image Processing, volume=6144,
pages=61443F, year=2006, organization=International Society for Optics and
Photonics

@inproceedingskarnowski2006locating, title=Locating the optic nerve in retinal
images: comparing model-based and Bayesian decision methods, author=Karnowski,
Thomas P and Govindasamy, V Priya and Tobin, Kenneth W and Chaum, Edward,
booktitle=Engineering in Medicine and Biology Society, 2006. EMBS’06. 28th
Annual International Conference of the IEEE, pages=4436–4439, year=2006,
organization=IEEE

@articleniemeijer2005automatic, title=Automatic detection of red lesions in
digital color fundus photographs, author=Niemeijer, Meindert and Van Ginneken,
Bram and Staal, Joes and Suttorp-Schulten, Maria SA and Abràmoff, Michael D,
journal=IEEE Transactions on medical imaging, volume=24, number=5,
pages=584–592, year=2005, publisher=IEEE

@inproceedingsniemeijer2004comparative, title=Comparative study of retinal
vessel segmentation methods on a new publicly available database,
author=Niemeijer, Meindert and Staal, Joes and van Ginneken, Bram and Loog,
Marco and Abramoff, Michael D, booktitle=Medical Imaging 2004: Image
Processing, volume=5370, pages=648–657, year=2004, organization=International
Society for Optics and Photonics

@articlestaal2004ridge, title=Ridge-based vessel segmentation in color images
of the retina, author=Staal, Joes and Abràmoff, Michael D and Niemeijer,
Meindert and Viergever, Max A and Van Ginneken, Bram, journal=IEEE
transactions on medical imaging, volume=23, number=4, pages=501–509,
year=2004, publisher=IEEE

@inproceedingsgarcia2008automatic, title=Automatic detection of red lesions in
retinal images using a multilayer perceptron neural network, author=García,
María and Sánchez, Clara I and Lopez, Maria I and Diez, Ana and Hornero,
Roberto, booktitle=Engineering in Medicine and Biology Society, 2008. EMBS
2008. 30th Annual International Conference of the IEEE, pages=5425–5428,
year=2008, organization=IEEE

@articlebae2011study, title=A study on hemorrhage detection using hybrid
method in fundus images, author=Bae, Jang Pyo and Kim, Kwang Gi and Kang, Ho
Chul and Jeong, Chang Bu and Park, Kyu Hyung and Hwang, Jeong-Min,
journal=Journal of digital imaging, volume=24, number=3, pages=394–404,
year=2011, publisher=Springer

@inproceedingshatanaka2008improvement, title=Improvement of automated
detection method of hemorrhages in fundus images, author=Hatanaka, Yuji and
Nakagawa, Toshiaki and Hayashi, Yoshinori and Hara, Takeshi and Fujita,
Hiroshi, booktitle=Engineering in Medicine and Biology Society, 2008. EMBS
2008. 30th Annual International Conference of the IEEE, pages=5429–5432,
year=2008, organization=IEEE

@articleli2004automated, title=Automated feature extraction in color retinal
images by a model based approach, author=Li, Huiqi and Chutatape, Opas,
journal=IEEE Transactions on biomedical engineering, volume=51, number=2,
pages=246–254, year=2004, publisher=IEEE

@inproceedingszhang2005top, title=Top-down and bottom-up strategies in lesion
detection of background diabetic retinopathy, author=Zhang, Xiaohui and
Chutatape, Opas, booktitle=Computer Vision and Pattern Recognition, 2005. CVPR
2005. IEEE Computer Society Conference on, volume=2, pages=422–428, year=2005,
organization=IEEE

@articlelalonde2001fast, title=Fast and robust optic disc detection using
pyramidal decomposition and Hausdorff-based template matching, author=Lalonde,
Marc and Beaulieu, Mario and Gagnon, Langis, journal=IEEE transactions on
medical imaging, volume=20, number=11, pages=1193–1200, year=2001,
publisher=IEEE

@articlemookiah2013automated, title=Automated detection of optic disk in
retinal fundus images using intuitionistic fuzzy histon segmentation,
author=Mookiah, Muthu Rama Krishnan and Acharya, U Rajendra and Chua, Chua
Kuang and Min, Lim Choo and Ng, Eddie Yin-Kwee and Mushrif, Milind M and
Laude, Augustinus, journal=Proceedings of the Institution of Mechanical
Engineers, Part H: Journal of Engineering in Medicine, volume=227, number=1,
pages=37–49, year=2013, publisher=SAGE Publications Sage UK: London, England

@inproceedingsacharya2012application, title=Application of intuitionistic
fuzzy histon segmentation for the automated detection of optic disc in digital
fundus images, author=Acharya, U Rajendra and Chua, Chua Kuang and Min, Lim
Choo and Ng, EYK and Mushrif, Milind M and Laude, Augustinus and others,
booktitle=Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS
International Conference on, pages=444–447, year=2012, organization=IEEE

@inproceedingswalter2001segmentation, title=Segmentation of color fundus
images of the human retina: Detection of the optic disc and the vascular tree
using morphological techniques, author=Walter, Thomas and Klein, Jean-Claude,
booktitle=International Symposium on Medical Data Analysis, pages=282–287,
year=2001, organization=Springer

@articlemendels1999extraction, title=Extraction of the optic disk boundary in
digital fundus images, author=Mendels, F and Heneghan, C and Harper, P and
Reilly, R and Thiran, J, journal=Proceedings BMES/EMBS 1999, volume=2,
number=EPFL-CONF-86620, pages=1139, year=1999, publisher=IEEE

@articlericci2007retinal, title=Retinal blood vessel segmentation using line
operators and support vector classification, author=Ricci, Elisa and Perfetti,
Renzo, journal=IEEE transactions on medical imaging, volume=26, number=10,
pages=1357–1365, year=2007, publisher=IEEE @articlestaal2004ridge,
title=Ridge-based vessel segmentation in color images of the retina,
author=Staal, Joes and Abràmoff, Michael D and Niemeijer, Meindert and
Viergever, Max A and Van Ginneken, Bram, journal=IEEE transactions on medical
imaging, volume=23, number=4, pages=501–509, year=2004, publisher=IEEE

@articlehoover2003locating, title=Locating the optic nerve in a retinal image
using the fuzzy convergence of the blood vessels, author=Hoover, Adam and
Goldbaum, Michael, journal=IEEE transactions on medical imaging, volume=22,
number=8, pages=951–958, year=2003, publisher=IEEE

@articlehoover2000locating, title=Locating blood vessels in retinal images by
piecewise threshold probing of a matched filter response, author=Hoover, AD
and Kouznetsova, Valentina and Goldbaum, Michael, journal=IEEE Transactions on
Medical imaging, volume=19, number=3, pages=203–210, year=2000, publisher=IEEE
@articlejiang2003adaptive, title=Adaptive local thresholding by verification-
based multithreshold probing with application to vessel detection in retinal
images, author=Jiang, Xiaoyi and Mojon, Daniel, journal=IEEE Transactions on
Pattern Analysis and Machine Intelligence, volume=25, number=1, pages=131–137,
year=2003, publisher=IEEE

@articlemarin2011new, title=A new supervised method for blood vessel
segmentation in retinal images by using gray-level and moment invariants-based
features, author=Marín, Diego and Aquino, Arturo and Gegúndez-Arias, Manuel
Emilio and Bravo, José Manuel, journal=IEEE transactions on medical imaging,
volume=30, number=1, pages=146–158, year=2011, publisher=IEEE

@articleyoussif2008optic, title=Optic disc detection from normalized digital
fundus images by means of a vessels’ direction matched filter, author=Youssif,
Aliaa Abdel-Haleim Abdel-Razik and Ghalwash, Atef Zaki and Ghoneim, Amr Ahmed
Sabry Abdel-Rahman, journal=IEEE Transactions on Medical imaging, volume=27,
number=1, pages=11–18, year=2008, publisher=IEEE

@articlesinthanayothin2002automated, title=Automated detection of diabetic
retinopathy on digital fundus images, author=Sinthanayothin, Chanjira and
Boyce, James F and Williamson, Tom H and Cook, Helen L and Mensah, Evelyn and
Lal, Shantanu and Usher, David, journal=Diabetic medicine, volume=19,
number=2, pages=105–112, year=2002, publisher=Wiley Online Library

@articleaich2020multi, title=Multi-scale weight sharing network for image
recognition, author=Aich, Shubhra and Yamazaki, Masaki and Taniguchi, Yasuhiro
and Stavness, Ian, journal=Pattern Recognition Letters, volume=131,
pages=348–354, year=2020, publisher=Elsevier

@articlewalter2007automatic, title=Automatic detection of microaneurysms in
color fundus images, author=Walter, Thomas and Massin, Pascale and Erginay,
Ali and Ordonez, Richard and Jeulin, Clotilde and Klein, Jean-Claude,
journal=Medical image analysis, volume=11, number=6, pages=555–566, year=2007,
publisher=Elsevier @articledecenciere2014feedback, title=Feedback on a
publicly distributed image database: the Messidor database, author=Decencière,
Etienne and Zhang, Xiwei and Cazuguel, Guy and Lay, Bruno and Cochener,
Béatrice and Trone, Caroline and Gain, Philippe and Ordonez, Richard and
Massin, Pascale and Erginay, Ali and others, journal=Image Analysis &
Stereology, volume=33, number=3, pages=231–234, year=2014

@inproceedingsfreund2009automated, title=Automated detection of drusen in the
macula, author=Freund, David E and Bressler, Neil and Burlina, Philippe,
booktitle=Biomedical Imaging: From Nano to Macro, 2009. ISBI’09. IEEE
International Symposium on, pages=61–64, year=2009, organization=IEEE

@articlehansen2004diabetic, title=Diabetic retinopathy screening using digital
non-mydriatic fundus photography and automated image analysis, author=Hansen,
Anja B and Hartvig, Niels V and Jensen, Maja S and Borch-Johnsen, Knut and
Lund-Andersen, Henrik and Larsen, Michael, journal=Acta Ophthalmologica,
volume=82, number=6, pages=666–672, year=2004, publisher=Wiley Online Library

@articlelarsen2003automated, title=Automated detection of diabetic retinopathy
in a fundus photographic screening population, author=Larsen, Nicolai and
Godt, Jannik and Grunkin, Michael and Lund-Andersen, Henrik and Larsen,
Michael, journal=Investigative ophthalmology & visual science, volume=44,
number=2, pages=767–771, year=2003, publisher=The Association for Research in
Vision and Ophthalmology

@articleliou2014autoencoder, title=Autoencoder for words, author=Liou, Cheng-
Yuan and Cheng, Wei-Chen and Liou, Jiun-Wei and Liou, Daw-Ran,
journal=Neurocomputing, volume=139, pages=84–96, year=2014, publisher=Elsevier

@inproceedingsshan2016deep, title=A deep learning method for microaneurysm
detection in fundus images, author=Shan, Juan and Li, Lin, booktitle=Connected
Health: Applications, Systems and Engineering Technologies (CHASE), 2016 IEEE
First International Conference on, pages=357–358, year=2016, organization=IEEE

@articlelarsen2003automated2, title=Automated detection of fundus photographic
red lesions in diabetic retinopathy, author=Larsen, Michael and Godt, Jannik
and Larsen, Nicolai and Lund-Andersen, Henrik and Sjølie, Anne Katrin and
Agardh, Elisabet and Kalm, Helle and Grunkin, Michael and Owens, David R,
journal=Investigative ophthalmology & visual science, volume=44, number=2,
pages=761–766, year=2003, publisher=The Association for Research in Vision and
Ophthalmology

@articlenovo2009localisation, title=Localisation of the optic disc by means of
GA-optimised topological active nets, author=Novo, Jorge and Penedo, Manuel G
and Santos, J, journal=Image and Vision Computing, volume=27, number=10,
pages=1572–1584, year=2009, publisher=Elsevier

@articleal2009active, title=An active contour model for segmenting and
measuring retinal vessels, author=Al-Diri, Bashir and Hunter, Andrew and
Steel, David, journal=IEEE Transactions on Medical imaging, volume=28,
number=9, pages=1488–1497, year=2009, publisher=IEEE

@articlelam2010general, title=General retinal vessel segmentation using
regularization-based multiconcavity modeling, author=Lam, Benson SY and Gao,
Yongsheng and Liew, Alan Wee-Chung, journal=IEEE Transactions on Medical
Imaging, volume=29, number=7, pages=1369–1381, year=2010, publisher=IEEE

@articlewinder2009algorithms, title=Algorithms for digital image processing in
diabetic retinopathy, author=Winder, R John and Morrow, Philip J and
McRitchie, Ian N and Bailie, JR and Hart, Patricia M, journal=Computerized
medical imaging and graphics, volume=33, number=8, pages=608–622, year=2009,
publisher=Elsevier

@inproceedingsal2008reference, title=A reference data set for retinal vessel
profiles, author=Al-Diri, Bashir and Hunter, Andrew and Steel, David and
Habib, Maged and Hudaib, Taghread and Berry, Simon, booktitle=Engineering in
Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International
Conference of the IEEE, pages=2262–2265, year=2008, organization=IEEE

@articleniemeijer2010retinopathy, title=Retinopathy online challenge:
automatic detection of microaneurysms in digital color fundus photographs,
author=Niemeijer, Meindert and Van Ginneken, Bram and Cree, Michael J and
Mizutani, Atsushi and Quellec, Gwénolé and Sánchez, Clara I and Zhang, Bob and
Hornero, Roberto and Lamard, Mathieu and Muramatsu, Chisako and others,
journal=IEEE transactions on medical imaging, volume=29, number=1,
pages=185–195, year=2010, publisher=IEEE

@articlepires2014advancing, title=Advancing bag-of-visual-words
representations for lesion classification in retinal images, author=Pires,
Ramon and Jelinek, Herbert F and Wainer, Jacques and Valle, Eduardo and Rocha,
Anderson, journal=PloS one, volume=9, number=6, pages=e96814, year=2014,
publisher=Public Library of Science

@articleamin2017method, title=A method for the detection and classification of
diabetic retinopathy using structural predictors of bright lesions,
author=Amin, Javeria and Sharif, Muhammad and Yasmin, Mussarat and Ali, Hussam
and Fernandes, Steven Lawrence, journal=Journal of Computational Science,
volume=19, pages=153–164, year=2017, publisher=Elsevier

@articlemansour2017evolutionary, title=Evolutionary Computing Enriched
Computer-Aided Diagnosis System for Diabetic Retinopathy: A Survey,
author=Mansour, Romany F, journal=IEEE reviews in biomedical engineering,
volume=10, pages=334–349, year=2017, publisher=IEEE

@inproceedingsfumero2011rim, title=RIM-ONE: An open retinal image database for
optic nerve evaluation, author=Fumero, Francisco and Alayón, Silvia and
Sanchez, JL and Sigut, J and Gonzalez-Hernandez, M, booktitle=Computer-Based
Medical Systems (CBMS), 2011 24th International Symposium on, pages=1–6,
year=2011, organization=IEEE

@articlecarmona2008identification, title=Identification of the optic nerve
head with genetic algorithms, author=Carmona, Enrique J and Rincón, Mariano
and García-Feijoó, Julián and Martínez-de-la-Casa, José M, journal=Artificial
Intelligence in Medicine, volume=43, number=3, pages=243–259, year=2008,
publisher=Elsevier @articleorlando2018ensemble, title=An ensemble deep
learning based approach for red lesion detection in fundus images,
author=Orlando, José Ignacio and Prokofyeva, Elena and del Fresno, Mariana and
Blaschko, Matthew B, journal=Computer methods and programs in biomedicine,
volume=153, pages=115–127, year=2018, publisher=Elsevier

@articlesrivastava2015highway, title=Highway networks, author=Srivastava,
Rupesh Kumar and Greff, Klaus and Schmidhuber, Jürgen, journal=arXiv preprint
arXiv:1505.00387, year=2015

@inproceedingssrivastava2015using, title=Using deep learning for robustness to
parapapillary atrophy in optic disc segmentation, author=Srivastava, Ruchir
and Cheng, Jun and Wong, Damon WK and Liu, Jiang, booktitle=Biomedical Imaging
(ISBI), 2015 IEEE 12th International Symposium on, pages=768–771, year=2015,
organization=IEEE

@articlefoong2007rationale, title=Rationale and methodology for a population-
based study of eye diseases in Malay people: The Singapore Malay eye study
(SiMES), author=Foong, Athena WP and Saw, Seang-Mei and Loo, Jing-Liang and
Shen, Sunny and Loon, Seng-Chee and Rosman, Mohamad and Aung, Tin and Tan,
Donald TH and Tai, E Shyong and Wong, Tien Y, journal=Ophthalmic epidemiology,
volume=14, number=1, pages=25–35, year=2007, publisher=Taylor & Francis

@articlewang2017fast, title=A-fast-rcnn: Hard positive generation via
adversary for object detection, author=Wang, Xiaolong and Shrivastava, Abhinav
and Gupta, Abhinav, journal=arXiv preprint arXiv:1704.03414, volume=2,
year=2017

@articleuijlings2013selective, title=Selective search for object recognition,
author=Uijlings, Jasper RR and Van De Sande, Koen EA and Gevers, Theo and
Smeulders, Arnold WM, journal=International journal of computer vision,
volume=104, number=2, pages=154–171, year=2013, publisher=Springer

@articlealghamdi2016automatic, title=Automatic optic disc abnormality
detection in fundus images: a deep learning approach, author=Alghamdi, Hanan S
and Tang, Hongying Lilian and Waheeb, Saad A and Peto, Tunde, year=2016,
publisher=University of Iowa

@inproceedingsmikolov2010recurrent, title=Recurrent neural network based
language model, author=Mikolov, Tomáš and Karafiát, Martin and Burget, Lukáš
and Černockỳ, Jan and Khudanpur, Sanjeev, booktitle=Eleventh Annual Conference
of the International Speech Communication Association, year=2010

@articlesundermeyer2015feedforward, title=From feedforward to recurrent LSTM
neural networks for language modeling, author=Sundermeyer, Martin and Ney,
Hermann and Schlüter, Ralf, journal=IEEE Transactions on Audio, Speech, and
Language Processing, volume=23, number=3, pages=517–529, year=2015,
publisher=IEEE Press

@inproceedingslee2009convolutional, title=Convolutional deep belief networks
for scalable unsupervised learning of hierarchical representations,
author=Lee, Honglak and Grosse, Roger and Ranganath, Rajesh and Ng, Andrew Y,
booktitle=Proceedings of the 26th annual international conference on machine
learning, pages=609–616, year=2009, organization=ACM

@articlehutchinson2013tensor, title=Tensor deep stacking networks,
author=Hutchinson, Brian and Deng, Li and Yu, Dong, journal=IEEE Transactions
on Pattern Analysis and Machine Intelligence, volume=35, number=8,
pages=1944–1957, year=2013, publisher=IEEE

@inproceedingstang2011splat, title=Splat feature classification: Detection of
the presence of large retinal hemorrhages, author=Tang, Li and Niemeijer,
Meindert and Abràmoff, Michael D, booktitle=Biomedical Imaging: From Nano to
Macro, 2011 IEEE International Symposium on, pages=681–684, year=2011,
organization=IEEE

@articleyun2008identification, title=Identification of different stages of
diabetic retinopathy using retinal optical images, author=Yun, Wong Li and
Acharya, U Rajendra and Venkatesh, Yedatore V and Chee, Caroline and Min, Lim
Choo and Ng, E Yin Kwee, journal=Information sciences, volume=178, number=1,
pages=106–121, year=2008, publisher=Elsevier

@articleforacchia2004detection, title=Detection of optic disc in retinal
images by means of a geometrical model of vessel structure, author=Foracchia,
Marco and Grisan, Enrico and Ruggeri, Alfredo, journal=IEEE transactions on
medical imaging, volume=23, number=10, pages=1189–1195, year=2004,
publisher=IEEE

@articlebressler2004age, title=Age-Related Macular Degeneration Is the Leading
Cause of Blindness…, author=Bressler, Neil M, journal=Jama, volume=291,
number=15, pages=1900–1901, year=2004, publisher=American Medical Association

@articlejelinek2006automated, title=An automated microaneurysm detector as a
tool for identification of diabetic retinopathy in rural optometric practice,
author=Jelinek, Herbert J and Cree, Michael J and Worsley, David and Luckie,
Alan and Nixon, Peter, journal=Clinical and Experimental Optometry, volume=89,
number=5, pages=299–305, year=2006, publisher=Wiley Online Library

@articlemaher2015review, title=Review of automated detection for diabetes
retinopathy using fundus images, author=Maher, Raju and Kayte, Sangramsing and
Dhopeshwarkar, Dr Mukta, journal=International Journal of Advanced Research in
Computer Science and Software Engineering, volume=5, number=3, year=2015

@articleal2016diabetic, title=Diabetic macular edema grading based on deep
neural networks, author=Al-Bander, Baidaa and Al-Nuaimy, Waleed and Al-Taee,
Majid A and Williams, Bryan M and Zheng, Yalin, year=2016,
publisher=University of Iowa

@articleyun2008identification, title=Identification of different stages of
diabetic retinopathy using retinal optical images, author=Yun, Wong Li and
Acharya, U Rajendra and Venkatesh, Yedatore V and Chee, Caroline and Min, Lim
Choo and Ng, E Yin Kwee, journal=Information sciences, volume=178, number=1,
pages=106–121, year=2008, publisher=Elsevier

@articleromero2019entropy, title=Entropy rate superpixel classification for
automatic red lesion detection in fundus images, author=Romero-Oraá, Roberto
and Jiménez-García, Jorge and García, María and López-Gálvez, María I and
Oraá-Pérez, Javier and Hornero, Roberto, journal=Entropy, volume=21, number=4,
pages=417, year=2019, publisher=Multidisciplinary Digital Publishing Institute