# Design and construction of the POLAR detector

N. PRODUIT<EMAIL_ADDRESS>T.W. BAO  T. BATSCH  T. BERNASCONI  I.
BRITVICH  F. CADOUX  I. CERNUDA  J.Y. CHAI  Y.W. DONG  N. GAUVIN  W. HAJDAS
M. KOLE  M.N. KONG  R. KRAMERT  L. LI  J.T. LIU  X. LIU  R. MARCINKOWSKI  S.
ORSI  M. POHL  D. RAPIN  D. RYBKA  A. RUTCZYNSKA  H.L. SHI  P. SOCHA  J.C. SUN
L.M. SONG  J. SZABELSKI  I. TRASEIRA  H.L. XIAO  R.J. WANG  X. WEN  B.B. WU
L. ZHANG  L.Y. ZHANG  S.N. ZHANG  Y.J. ZHANG  A. ZWOLINSKA  University of
Geneva, Geneva Observatory, ISDC, 16, Chemin d’Ecogia, 1290 Versoix
Switzerland  University of Geneva, Département de physique Nucléaire et
Corpusculaire (DPNC), quai Ernest-Ansermet 24, 1205 Geneva, Switzerland  Paul
Scherrer Institut 5232 Villigen PSI, Switzerland  Key Laboratory of Particle
Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences,
Beijing, China, 100049  National Centre for Nuclear Research ul. A. Soltana 7,
05-400 Otwock, Swierk, Poland

###### Abstract

The POLAR detector is a space based Gamma Ray Burst (GRB) polarimeter with a
wide field of view, which covers almost half the sky. The instrument uses
Compton scattering of gamma rays on a plastic scintillator hodoscope to
measure the polarization of the incoming photons. The instrument has been
successfully launched on board of the Chinese space laboratory Tiangong 2 on
September 15, 2016. The construction of the instrument components is described
in this article. Details are provided on problems encountered during the
construction phase and their solutions. Initial performance of the instrument
in orbit is as expected from ground tests and Monte Carlo simulation.

###### keywords:

Polarimeter , X-rays , Compton scattering

††journal: Nuclear Instruments and Methods

##  1 Introduction

POLAR is a GRB polarimeter, which implements the conceptual design described
in reference [1]. The basic concept is to measure the mean degree of
polarization and the azimuthal angle of the polarization vector by analyzing
the angular distribution of the azimuthal Compton scattering angle of a sample
of photons associated with a GRB. This requires that both the recoil electron
from the Compton process and a secondary interaction of the outgoing photon
are observed. POLAR uses the same plastic scintillator material for both, and
determines the azimuthal scattering angle by structuring the target into
40$\times$40 pixels read out separately. The detector is sensitive to gamma
rays with an energy between a 10 keV and 500 keV. Its field of view covers
almost half the sky.

POLAR was chosen by the Chinese authorities to be one of the instruments on
board of the Chinese space laboratory Tiangong 2 (TG-2). The laboratory and
its payloads were successfully launched on September 15, 2016 into a low Earth
orbit (300 km altitude 45 degree inclination).

##  2 POLAR models

Following this design concept, a demonstrator with only 8$\times$8 pixels was
first produced and tested in a polarized gamma ray beam at the European
Synchrotron Radiation Facility (ESRF) as described in [2]. These tests
demonstrated a good agreement between the produced hardware performance and
the Monte-Carlo results.

Several models of the complete POLAR detector were then produced. A
qualification model (QM), was used to demonstrate the performance of the
instrument at a beam test at ESRF [2]. Afterwards this QM underwent all the
qualification procedures performed at SERMS Terni. This instrument
qualification consisted of both random and sinusoidal vibration tests,
electromagnetic compatibility (EMC) tests, a thermal cycle test, a thermal
vacuum test, and shock tests in the direction perpendicular to the bars.
During the last shock test, consisting of a 500 $g$ shock in the direction
along the scintillation bars, the instrument suffered a catastrophic
mechanical failure.

After this incident, the shock mitigation concept was fully redesigned as
described in Section 3. All the individual design changes where separately
tested using dedicated vibration and shock equipment. The upgraded model
underwent all qualification tests successfully, including a shock test in the
Z direction. This model was subsequently used as the flight spare model (FMS).

A copy of this instrument was produced as the flight model (FM). A batch of
less stringent flight acceptance tests were performed on this model. The FM
was fully calibrated using a 100% polarized beam at the ESRF facility. The
calibration of the flight model will be described elsewhere [3].

Using the GEANT4 package [4], a complete model of the POLAR set-up was
constructed to provide a high reliable simulation of its properties and
performance. The fidelity of the model and residual systematic were
demonstrated using data from the ESRF calibration of the FM [5].

##  3 Overall design

As GRBs appear randomly in the sky and for a very short instant (milliseconds
to minutes), a large field of view (FoV) is required for the polarimeter in
order to detect as many GRBs as possible. The FoV of POLAR is almost half of
the sky, as detailed in [1].

POLAR is mounted on the Tiangong 2 Chinese space laboratory which was launched
into Low Earth Orbit on September 15, 2016. The instrument is composed of two
parts, the OBOX assembly, which consists of the target and associated
electronics and the IBOX assembly which contains ancillary instrumentation as
well as the space craft interfaces. The two assemblies are connected by a
harness for power, data and command transmission.

##  4 OBOX assembly

Figure 1: OBOX assembly

OBOX is mounted on the outer surface of TG-2 through 20 shock absorbers as
shown in figure 1. It is connected to IBOX with two electrical cable bundles
for separate power and data transmission. OBOX is composed of the following
parts displayed in the figure and detailed in the following:

  * 1.

the aluminum frame containing the electronics (POLAR GRID);

  * 2.

the target with its 25 modules;

  * 3.

the top cover covered by a multi-layer insulation fabric (MLI).

Each one of the 25 identical target modules (see figure 2) consist of 64
scintillation bars optically coupled to a multi-anode photo-multiplier (MAPM)
with 64 separate readout channels. Each module is packaged in its own 1 mm
thick Carbon Fiber Reinforced Polymer (CFRP) box which also contains the
front-end boards with high voltage (HV) distribution, pre-amplification and
digitization. All elements used in the construction are detailed in the
following sections.

###  4.1 Aluminum frame

The aluminum frame is the main mechanical support of OBOX. The alloy AL
7075T7351 was chosen, among other reasons, for its low level of activatable
isotopes such as manganese. As can be seen in figure 1 it consists of four
pockets surrounding a central grid. The four pockets, when viewed from the
back of the instrument contain (in clock-wise order when looking towards the
zenith direction): the central computer (CT), the high voltage power supply
(HV PS), the low voltage power supply (LV PS) and the cabling pocket with the
connectors for the cable harness to IBOX. The central grid serves as a
mechanical support for the 25 detector modules (see Section 5). The aluminum
frame also conducts the heat generated by modules and electronics to TG-2.
Heat is furthermore lost through radiation through white paint on the exposed
surfaces (see Section 4.1.2.) The Aluminum frame is suspended on top of TG-2
using shock dampers. The shock dampers are constructed connecting two coaxial
cylinders within a hollow cylinder of rubber. This is a rather standard design
that gives three-dimensional elastic connection between the central screw and
the object to be suspended. The rubber material was provided by the Chinese
space authorities, respecting their requirements for out-gassing and time
degradation. A MLI curtain protects the rubber against direct solar
irradiation.

####  4.1.1 Venting

Under atmospheric pressure, the aluminum frame and the modules contain several
liters of air that must be vented during the ascent. The pressure drop during
a typical launch is rapid requiring the venting devices to be able to release
the internal pressure efficiently while at the same time not allowing external
light to enter the instrument. In total 4 venting devices, all designed and
manufactured in Geneva university, are present in OBOX: two venting devices on
the aluminum grid and two on the carbon cover. The two venting devices on the
aluminum frame, located in quadrant 1 and 3, are formed by hollow screws. The
opening inside the screw has the shape of a maze which is painted black. The
hole size was calculated such that the speed of the escaping air will stay
well below the speed of sound during ascent but, at the same time, the size of
the holes must be smaller then the Debye length of the plasma typical at our
orbit (centimeters) to prevent ions to penetrate inside OBOX [6]. The two
venting devices mounted on the carbon cover are simple hollow CFRP covers with
a hole on the side.

####  4.1.2 Paint

A special paint (GS121FD from the MAP French company) has been applied to the
aluminum frame. The paint has a white color in visible light and a grainy
texture. Its emmisivity (0.8) and reflectivity (0.2) was chosen so that it
radiates heat to the deep space. The Solar absorption coefficient after
application and drying is a modest 0.2. The cooling of OBOX is completely
passive and relies mostly on the characteristic of this paint. A secondary
function of the applied paint is the protection of the aluminum frame against
atomic oxygen chemical attack.

The painted assembly was simulated in a thermo-mechanical model and subjected
to a thermo-vacuum test for verification. The test was performed on a properly
painted model featuring the correct MLI covering and thus is representative of
the thermal performance during the night part of the orbit. Initial thermal
performance of the instrument in space is in agreement with calculations. The
full thermal performance of POLAR in space will be addressed in a separate
paper.

The paint used on the aluminum frame is fragile and can be very easily
scratched. On FM, the paint was applied at the latest possible moment just
before shipping to China. Last minute repairs of handling scratches were
executed at the launch pad just days before attaching OBOX to Tiangong 2.

###  4.2 Top cover

Between the target and the MLI, a cover provides light tightness and
mechanical strength, and shields from low energy particles. It consists of
CFRP of 1 mm thickness. Its main purpose is to passively reduce the flux of
electrons with energies below 1 MeV which populate the radiation belts.
Without shielding it was shown in [1] that the high flux of these particles
can induce random coincidences indistinguishable from Compton scattering
photons.

The cover also provides mechanical stability to fix the 25 modules in place
and reduce the vibrations encountered during launch. The back end of each
module is fixed to the cover by one M3 screw.

###  4.3 MLI

The unpainted CFRP surfaces of POLAR are covered by a multi-layer insulation
foil (MLI). The MLI is composed of 15 layers of 50 $\mu$m polyimide film. The
top layer features a light reflection sheet of 6 $\mu$m polyester. The goal of
this MLI is to thermally isolate the target from its surrounding. In
simulation, the MLI is considered as a perfect absorber for heat conduction in
both directions. The MLI is also protecting again micrometeorite impacts and
absorbs very low energy electrons.

##  5 Target modules

For modularity and redundancy, the photon target is segmented in 25 modules.
Each module (see Figure 2.) is an independent sensitive unit with its own
plastic scintillator hodoscope and its own front-end electronic (FEE). The
modules communicate only digitally with the rest of the system. Each module is
enclosed in its own container such that it forms a fully functional
transportable object.

Figure 2: Exploding view of one module.

###  5.1 Module shock absorbers

The screw connecting the module to the CFRP cover connects to a plastic piece
made of Polyether ether ketone (PEEK) (end plate, 2mm) placed at the top end
inside the module. Below the end plate is a bumper which was made of rubber
material for the first QM which suffered catastrophic loss of all MAPM. Rubber
is an almost uncompressible material with a Poisson modulus of 0.4999. Thus
under longitudinal pressure, rubber expands sideways but the same volume. If
the rubber is laterally constraint it thus becomes in-compressible. This
caused the failure of first QM to withstand shocks in the longitudinal
direction.

The damping rubber (3mm) was thus cut into 16 square pieces with clearance
between them. This allows for a side-way expansion of the rubber, efficiently
dissipating the energy of lateral shocks.

This solution alone was calculated to be sufficient to cure the problems
encountered in the shock test of QM. However a further safety margin was
produced by several additional improvements. Rubber was replaced by Sorbothane
(produced by Sorbothane, Incorporated) which has better dissipation
properties. The rigidity of the aluminum grid holding modules was also
increased by adding ridges.

Both the PEEK and the rubber absorbers are kept as thin as possible to
minimize the absorption incoming photons. The materials add an extra 8%
attenuation for 50 keV photons coming from zenith.

###  5.2 Baffles

Two baffles (front baffle and MAPM baffle) made of Polyurethane (PU5286 from
Huntsman Company) with 64 square holes are very precisely manufactured by
additive technology. They mechanically fix the 64 bars in place. The front
baffle connects to the shock absorbers described above and the bottom grid
rests on the MAPM with the optical pad in-between. The grid structure of the
baffles ensures that every scintillation bar is well centered on the
structured cathode of the MAPM.

###  5.3 Scintillating bars

The active material in one module consists of 64 bars of scintillating
material EJ-248M made by Eljen Technology, a scintillator type which is
resistent to high temperatures. The high temperature material was chosen as in
the lab creeping of the non high temperature resistant version of the material
at temperatures as low as 40 degrees was observed and POLAR was required to be
capable of storage temperatures up to 60 degrees. The shape of the
scintillators is a rectangular cuboid of length 176 mm and $5.8\times 5.8$ mm2
surface dimensions. The attenuation length of visible light in the
scintillation material is 1.6 meter and is not a significant concern for these
short bars.

Both ends of each bar are truncated into a conical shape over the last 4 mm to
end up with lateral dimension of 5$\times$5 mm2 which matches the size of the
MAPM cathode pixel. The far end conical shape is useful for mechanical support
and was shown ([5]) to enhance the uniformity of the optical yield.

The scintillation yield of this material is one visible photon per 108 eV of
electromagnetic energy deposition. X-ray photons of interest for POLAR range
between 10 keV and 500 keV in energy. These photons interact with the bar
material either by photo-electric effect or by Compton scattering. In both
cases an electron is produced in the scintillation material. The range of the
produced electrons is typically much lower than the dimension of the bar.
Their complete energy is thus typically deposited in a single bar. The light
yield of scintillators is not fully linear but depends on the density of the
energy deposition by Birks effect [7]. The POLAR Monte Carlo simulation takes
into account this important detail [5].

Scintillation photons are emitted isotropically and when reaching the bar
surface under a shallow angle will be totally reflected. Such photons are
transmitted to the end of the bar in an essentially loss-free way. The quality
surface finish of the bars is essential to guarantee that the collection
efficiency of the visible photon does not depend on the location of the energy
deposition. The scintillation bars are produced in form of a plate with the
correct 5.8 mm thickness. These plates were then diamond cut into bars. For
two surfaces, the mirror finish is thus guaranteed by the production process.
The two other surfaces were polished to ensure a mirror finish. The roughness
of one bar was measured with a scanning micrometer device. The distribution of
the normal angle was measured by differentiation of the height versus distance
curve. It was found that for the two good surfaces, the distribution of the
normal angle is Gaussian with a width of 2.1 10-5 rad. For the manual polished
surfaces a width of 2.6 10-4 rad was found.

Those measured values are used in the GEANT4 based Monte Carlo. The
simulations have shown that the surface smoothness is an important parameter
for the performance of POLAR. However, when the smoothness is better than 5
10-4 rad results become insensitive to this parameter. The two conical ends of
the bar are also machined and polished.

###  5.4 Vikuiti reflective foil

Photons leaving a scintillator bar, either laterally beyond the total
reflection angle or longitudinally at the far end, must be prevented from
entering into adjacent bars or getting lost. For this purpose each bars is
wrapped with an opaque and highly reflective material.

As a high performance reflector the material “Vikuiti Enhanced Specular
Reflector Film (ESR)” from 3M company was chosen [8]. Vikuiti provides mirror-
like ultra-high reflectivity of greater than 98% over the full visible
spectrum and all incident angles. To not prevent total reflection at glancing
angles, the Vikuiti is not attached to the bar.

###  5.5 Optical coupling pad

At the bottom end of the bar the optical photons should penetrate into the
MAPM without reflection, using an optical coupling matching the indices of
refraction of the materials. Non-liquid soft materials with the correct index
of refraction were investigated and a solution designed and successfully
tested in space for the AMS detector [9] was chosen. Soft transparent pads of
0.7 mm thickness were constructed by curing the two component material Dow
Corning 93-500 [10] at moderate temperature under vacuum.

The mechanics of the bar mounting ensures that the bars apply a small pressure
to this interface material at all times even during vibrations. This ensures
that there is no interface where internal reflection can take place.

Optical photons arriving at the MAPM end of the bars penetrating the interface
material can diffuse sideways and hit neighboring anode pads. The probability
depends on the exiting angle from the scintillator bars. This creates optical
cross talk to neighboring channels, which is highly undesirable as it dilutes
the signal, blurs the position accuracy and reduces the energy resolution.
This optical cross talk is proportional to the total distance between the bar
end and the cathode pad inside the MAPM. This distance is therefore minimized.
It is furthermore important that the positioning baffle is opaque. This
optical cross talk is inevitable and reduces the performance of the
instrument.

###  5.6 Multi-Anode Photo-Multiplier (MAPM)

The MAPM transforms the optical photons from the scintillator into a
measurable electrical charge. The multi-anode metal mesh photo-multiplier type
HAMAMATSU R10551-00-M64 [11] was chosen for POLAR. This photo-multiplier has
64 anode in a flat panel square assembly. It features 64 independent cathodes
of dimensions 6.08$\times$6.08 mm, 12 dynodes and a grid and 64 independent
anodes. Each channel can provide a gain of up to 1.5 $\cdot 10^{6}$. With each
MAPM, the HAMAMATSU company provides a measure of the cathode luminosity
(typically 60 $\mu$A/lm), and a uniformity map. For POLAR a maximum gain ratio
of 2 between all channels within a MAPM was specified. The best MAPM were
selected based on the properties provided by HAMAMATSU for the POLAR flight
model. The MAPM has an electrical cross talk at the percent level, negligible
compared to the optical cross talk mentioned above.

###  5.7 Front-End Electronic (FEE)

The front-end electronics (FEE) was designed with these particularities in
mind (see also [12]):

  * 1.

It must be completely conduction cooled.

  * 2.

It must work at atmospheric pressure as well as in vacuum. Operation at the
most demanding pressure for high voltage sparking, around 1mbar, is not
required.

  * 3.

The lateral dimension must be compatible with the MAPM dimensions to enable 4
side buttability.

  * 4.

The communication is fully digital.

  * 5.

It can work and retain its performance (gain and dynamic range) in an extended
temperature range (-40∘ to +60∘)

  * 6.

It withstands 5 years of low Earth orbit (krad level) radiation without
visible gain degradation.

  * 7.

It can withstand random vibrations of the order of 20 $g$ and shocks of the
order of 500 $g$.

The FEE consists of three stacked PCB boards held together from two sides by
an aluminum flange that serves as a mechanical structure and provides thermal
contact to the rest of OBOX. The three boards of the FEE are described below.

####  5.7.1 HV distributor board

The high voltage distribution board is situated directly behind the MAPM. All
the MAPM pins connect directly to the board by means of gold tulip connectors.
The anode signal is capacitively decoupled with 330 pF and 100 $\Omega$ to
ground. The signal from dynode 12 is capacitively coupled with 4.7 nF and 10
k$\Omega$ to ground. The high voltage arrives to the board via a coaxial
cable. The inner conductor of the coaxial cable is directly soldered on the
board. The shield of the coaxial cable is soldered but not connected as it
would make a ground loop with the local ground of the board (see Section 8.1).
The HV goes to the cathode through a 100 M$\Omega$ resistor. This line is
capacitively coupled to ground by three high voltage capacitors of 12 nF. All
noise on this line couples directly to every anode output so this is a
critical signal for performance.

The dynode high voltage divider consists of twelve 470 k$\Omega$ resistors.
Further resistors and capacitors are used in the dynode chain for enhancing
high rate performance.

The HV distributor board contains no active component but is densely populated
with passive components and connections. The power dissipation of is limited
to 0.1 W, so that it can be easily conducted through the connectors and the
aluminum flange. The HV board is connected to the subsequent FPGA board
through two SAMTEC 40 pin connectors.

####  5.7.2 FPGA board

The FPGA board takes care of the signal shaping, digitization, the trigger
decision and the communication to the rest of the set-up. The 64 anode signals
arrive at a readout chip (VA) from the Viking family [13]. This chip is a 64
channel shaper, discriminator, sample and hold and analog multiplexer from the
IDEAS company. The chip requires a -2.5 V, ground and -1.5 V power supply,
which is provided by the third board of the FEE assembly described below. The
chip die is directly glued to a gold contact on the PCB and connected by gold
wire bonding.

The analog output of the Front-End chip is digitized by a 25 Ms/s 14 bit ADC.
The sequencing of the readout, the trigger logic decisions and the data
compression are taken care of by a AGL250V2 FPGA (AGL) [14]. The trigger is
based on signals from very fast discriminators, which transmit to the AGL the
multiplicity of channels over threshold. The FPGA receives within 30 ns a
signal that says if there is at least 1 channel, 2 channels or more than 8
channels above threshold. The number of channels quoted here are the default
values on a programmable DAC, these settings can be changed. All analog
signals to the VA like the overall threshold are also programmable by DAC. The
AGL implements the trigger logic and all the communication to the outside.

As soon as one channel is above threshold, the 64 VA channels are put into
hold. This state stays put until the higher level trigger takes a decision. If
the decision is positive, a full readout occurs which lasts for 6
microseconds. if the decision is negative the VA chip resumes live operation.
The AGL maintains also a counter to measure dead time. A LS64 chip (produced
by the same company which produced the VA) is used for level shifting of the
64 discriminator outputs between the non-matching voltage levels of the VA and
the AGL. Connection to the LS64 is made by direct wire bonds. All wire-
bounding schemes have been tested for vibration.

The FPGA board also contains a digital thermometer, featuring a unique
readable digital ID that is used to identify each FEE assembly.

####  5.7.3 Power regulation and connector board

The third board of the FEE assembly provides a space qualified connector
between the module and the rest of OBOX and to filter and recondition the
voltage level received from the low voltage power supply.

##  6 OBOX back-end electronics

The low voltage power supply (LV PS) was specified to respect the desired
size, operation, interface and space qualification requirements. These
specifications were provided to “Art of Technology”, a company based in Zurich
[15] for design, engineering and board production. The LV PS independently
generates three voltages for each FEE (+3.3, +2 and -2.5). A single +28V input
is provided to the LV PS from IBOX (see Section 10). The output voltages are
stable to within 1% and independently switchable.
The high voltage power supply board (HV PS) was produced by the same company
that produced the LV PS. The HV PS works in two stages. First a global high
voltage level is produced (settable between 600 V and 1200 V), subsequently 25
current limited sources (settable between 0 and 200 $\mu$A) are derived from
this high voltage and provided to individual MAPMs. As the MAPM voltage supply
is essentially an Ohmic load, a current source corresponds to a voltage
source. The HV PS current sources makes heavy use of opto-coupler transistors
to regulate the current. Initially worries existed that the transistor gain
would change with irradiation, which would compromise the long term stability
of the high voltage. A large batch was therefore irradiated up to 5 krad using
the gamma-ray therapy facility of the Geneva hospital oncology department.
This test have shown no important degradation. The 25 FEE assemblies are
connected to the HVPS by coaxial cables. They are connected to the CT and to
the LV PS using five flexible PCB cables (flex).

###  6.1 Central computer (CT)

The central computer (CT) is described in more details in [16]. The CT has
several roles in POLAR:

  * 1.

It receives and treats all commands from IBOX.

  * 2.

It pilots the HV PS and the LV PS.

  * 3.

It synchronizes the FEEs by distributing a common clock.

  * 4.

It answers promptly to trigger request from all the 25 FEE and implements the
overall event trigger logic.

  * 5.

When events are in the FEE buffer these are read out and combined into science
packets containing both the FEE events and the trigger decisions.

  * 6.

Periodically all temperature sensors are read out as well as the status of the
FEEs. The CT builds the housekeeping telemetry packets.

  * 7.

It sends science and housekeeping telemetry packets to IBOX.

The CT tasks are distributed to three FPGAs: the computer FPGA (CPU), the
trigger FPGA (TRIG) FPGA and the communication FPGA (COM). All FPGA are of the
type A3PE3000L-FG484I. A block diagram of the CT functionality and
connectivity is shown in Figure 3.

Figure 3: Functional block diagram of the POLAR CT.

####  6.1.1 CT board

The CT is constructed using surface mounted chips on a 8 layers PCB as
described in [16], providing two-fold redundancy. Apart from the three FPGAs
it features a very stable crystal clock, fifty Low Voltage Differential
signaling (LVDS) level shifter to establish LVDS bidirectional communication
with FEE assemblies, one temperature sensor and SPI and I2C drivers to
communicate with LV PS and HV PS. On power-up, the CT is in a in cold spare
state.

####  6.1.2 Connectors

The CT receives or drives up to 500 real time signals from the FEE assemblies
through the flex cables. For this purpose ten high density nano-size
connectors are used (type 891-007-51S-A2-BST-1-J and 891-007-25S-A2-BST-1).
These connectors are rather fragile and susceptible to short circuits between
connections. The number of mating and unmating actions on the FM and FMS thus
had to be strictly limited and documented and extreme care was taken for each
connection to a flex cable.

####  6.1.3 CPU

The CPU FPGA acts as a computer. It communicates through LVDS with IBOX,
receives and interprets all commands from IBOX, is the master of the LV PS and
HV PS, surveys all temperatures, builds housekeeping telemetry and sends
prepared science packets to IBOX. The CT is also able to work completely
independently when booted.

####  6.1.4 Trigger

The trigger FPGA implements the instrument trigger logic. As soon as a FEE has
at least one channel with a signal over threshold, the FEE sends a demand for
treatment to the trigger FPGA. Subsequently the FPGA waits 100 ns to see if a
demand comes from another module. It then sends a positive or a negative
answer to all waiting modules. The answer is based on the multiplicity
communicated by each waiting FEE. If one waiting FEE has a large multiplicity,
the event is rejected apart from a pre-selected fraction. The pre-scaling
value can be set by the user.

If at least two FEEs have a multiplicity higher than one but below the high
multiplicity threshold, the event is accepted. If at least one FEE has a
multiplicity of two, the event is also accepted. If only one module is waiting
and it has a multiplicity of 1 the event is pre-scaled. Also for this the
fraction of stored events can be set by the user.

The trigger FPGA distributes a master clock to every FEE. The clock signal is
used by the FEE to time-stamp the events and to compute a dead time. Each time
the trigger FPGA takes a decision it creates a time-stamped trigger packet
explaining the decision. In standard operation the trigger FPGA does not
produce trigger packets for rejected events. The trigger FPGA also measures
its own dead time. However the dead time in POLAR is dominated by the dead
time from the FEEs and the trigger FPGA dead time is negligible.

####  6.1.5 Communication

The communication FPGA continuously checks the 25 FEEs for events waiting to
be processed. If this is the case, the event is read out and put into a FIFO
for the trigger FPGA to decide and forward it to IBOX. The communication FPGA
can sustain 25 communications in parallel. If the FIFO is full, the trigger
FPGA will not accept further events.

####  6.1.6 Science data

The CT is just moving packets from FEE to IBOX communication. However, it adds
to this data stream a data stream coming from the trigger decision one packet
per positive event trigger decision. A physical event corresponds to one
trigger packet together with 1 to 25 module packets.

####  6.1.7 Clock distribution

The CT has also the task of maintaining an absolute time reference. The CT
features a very stable ($10^{-6}$) quartz oscillator. Oscillations are counted
at a 12.5 MHz frequency and this count is attached to every event. IBOX is
sending every two minutes to OBOX a synchronization (SYNC) command that is
very precisely timed versus the arrival of a pulse per second pulse from a
Global Positioning system (GPS) receiver. OBOX is storing the counter value
each time a SYNC command arrives and this value is sent in the housekeeping
telemetry.

####  6.1.8 Commanding

The CT receives commands from IBOX, decodes them and implements them. If the
command is decoded and understood correctly an acknowledge packet is created
for every received command. Most of the commands just write a parameter to a
register which will be used for FEE initialization. The CT has four different
states: Booting, Data Acquisition (DAQ), maintenance, calibration. The
commands “go the maintenance mode”, “SYNC” and “read register” can be received
at any time. All other commands (“write register”, “start LV PS”, “start HV
PS”, “go to DAQ mode”, “go to calibration mode” can be received only in
maintenance mode.

###  6.2 Heaters

Heaters in the form of a resistance printed on a kapton foil are glued on the
inside of the four pockets housing the OBOX back-end electronics in the
aluminum frame. The goal is to provide heating power inside OBOX in case of
low temperatures which could damage the instrument. Each heater resistance is
160 $\Omega$ for a total resistance of 40 $\Omega$ delivering 20W from the
nominal 28V supply. The heaters are piloted from IBOX. IBOX is also measuring
the temperature of the aluminum frame using two PT100 resistors and
automatically supplies power when the temperatures drop below a settable
threshold.

####  6.2.1 Outside Connectors

OBOX features 3 connectors on the outside. One (X2) is the power connector
through which OBOX receives the main 28V hot and 28V cold power from IBOX.
Each electrical connections uses two conductors for redundancy. The hot and
cold power supply are never used at the same time. The X2 connector brings
also power to the internal heaters and connections to the two PT100
temperature measuring resistances.

The X1 connector provides four bidirectional LVDS communication channels to
the platform. Two bidirectional channels are connected to the hot CT and two
to the cold CT. A third connector is used to flash the 3 FPGAs of the hot and
the 3 FPGAs of the cold CT. On FM, this connector was masked just before the
launch because in flight condition it does not connect to anything.

####  6.2.2 Filters

During EMC tests some filtering turned out to be necessary on the main 28V
power supply to withstand the rather drastic transients that they have to cope
with. All power lines go first through a ferrit coil, then all 28V power lines
go through a filter of type Tusonix 4209-053LF. The 28V lines are capacitively
coupled to ground through a four-capacitor circuit with 2 parallel of 2 serial
capacitors, which can withstand any single capacitor failure and some double
capacitor failures. The equivalent capacitance is 2.2 $\mu$F rated up to 100V.

##  7 Redundancy Scheme

The instrument was designed to be fully redundant to allow for small
malfunctions, by eliminating single point failures as far as possible. The
split into 25 identical target modules (see Section 5) already provides
redundancy. In case one module stops working, POLAR loses between 4% (The
surface of one out of 25 modules is lost) and 8% (this module cannot
participate to 2 modules events) of its sensitivity depending on position.

The LVPS is twofold redundant in its first stage in addition to the 25-fold
redundancy of the target modules. The first stage of the HVPS supply has a
constant hot spare and the 25 current limiters are duplicated as cold spares.

There are two identical CT (see Section 6.1) in cold redundancy. All the power
cabling is doubled. Communication between OBOX and IBOX also has a cold spare.
Both the cold and the hot communication channels are implemented with two
redundant channels. The first channel which passes a validated packet is
retained as the active channel.

Most of the electronic components used are Commercial off-the-shelf (COTS) but
industrial quality is used when existing. Some components are determined to be
suceptible to create a major failure, for those military level components are
used mostly in the HV power supply. Components like the VA and the LS64 where
qualified by the collaboration.

##  8 Electrical and thermal coupling

The coupling between the module and the aluminum frame must provide both a
good ground connection and good thermal coupling. It must furthermore ensure
that the modules stay aligned even after the vibration of launch. For these
purposes the material Therm-a-gap [17] was chosen, which remains soft under
compression and has a high thermal and electrical conductivity. The thickness
of the Therm-a-gap is 4 mm and pressure is applied using the screw connecting
the module to the carbon cover, controlled by the torque applied to the screw.

###  8.1 Grounding scheme

The signals to be measured by POLAR electronics are of the order of fC, such
that an optimum grounding scheme is required. While in-orbit OBOX is exposed
to free electrons and atomic oxygen. This means that high resistivity material
should be protected and every conductor should be ohmically connected to
ground.

The reference ground is the ground from the power cable. The aluminum grid is
connected to ground at a single point with a 1k$\Omega$ resistor. The CFRP
OBOX cover, which is an electric conductor, is connected to the aluminum
frame. This creates a full Faraday cage around OBOX.

All communication uses LVDS signals. This way the communication relies only on
the difference between two voltages and not on a level versus ground.

##  9 Calibration sources

Weak radioactive sources of 22Na where prepared by cutting a 1 MBq 22Na mother
source. The mother source was ground to dust, which was recovered using
adhesive kapton tape. Each of the sources was glued inside an L-shaped piece
of copper of 200 $\mu$m thickness. The copper prevents any positron from
escaping and provides a pure source of 511 keV photon pairs. Eight sources
with appropriate activities between 100 and 200 Bq were selected and glued in
FMS and FM into positions indicated by the star symbols in Figure 4.

22Na was chosen because it creates two coincident back to back photons of 511
keV. This allows for the event topology of two energy depositions lying on a
line passing near the calibration source to be used to extract those rare
events.

Figure 4: Numbering of target modules in the Flight Model. The z axis,
corresponding to the zenith direction under normal flight conditions, points
into the page.

##  10 IBOX

IBOX is mounted in the interior of TG-2, the flight model is shown in Figure
5. The two main parts of IBOX are a control unit and a low-voltage power
supply. The control unit is responsible for the data management of POLAR using
LVDS bus communication with the satellite platform and OBOX. Slow control is
monitored using a MIL-STD-1553b (1553b) communication channel. It furthermore
handles reception and execution of commands uploaded to IBOX from ground and
the overall system monitoring and handling. The low-voltage power supply
provides all required voltages for both OBOX and IBOX itself. IBOX is
assembled with a food steamer structure, of 5 layers in total. From top to
bottom: the top cover, a hot control unit, a cold control unit, the low-
voltage power supply and a floor plate. The gross weight is 3.7 kg and the
size is $247\times 160\times 85$ mm3.

Figure 5: Image of IBOX Flight Model.

IBOX contains two software configuration items: microcomputer software and
FPGA firmware. The microcontroler software is mainly responsible for the
communication of the 1553b bus, undertaking the data interaction between the
satellite platform and FPGA logic. The FPGA firmware, as the control core of
IBOX, receives housekeeping data and science data from OBOX, offers relevant
telemetry information to the satellite platform, manages all command
injections, gives signals of timing calibration, and judges entrance and exits
from the South Atlantic Anomaly (SAA) area where the HV of OBOX is switched on
or off. The SAA region is defined as a programmable rectangle in longitude
latitude. During operation, this was seen to be too restrictive and ground
commands were used to turn on and off HV to create a polygonal SAA region (see
also chapter on performances).
In the thermal design of IBOX heat is dissipated through conduction through
the bottom plate which is in thermal contact with the satellite platform. The
bottom plate has undergone oxidation treatment for electrical conductivity.
The other surfaces are blackened to improve the energy contact with the
platform through radiation while improving corrosion resistance of the
equipment. As the power consumption of IBOX is mainly dissipated through
contact conduction the low-voltage module is placed at the lowest layer, and
all heating devices are directly attached to the bottom plate and the side
walls. A thermally conductive silicone grease is applied between them.

##  11 Thermal design

OBOX is passively cooled using the white paint on the aluminum frame and the
contact through the shock dampers to the Tiangong 2 platform. In the design
the Tiangong 2 platform was considered as an infinite heat bath of constant
temperature. All the non-painted parts of POLAR are shielded with MLI and
therefore don’t participate in the thermal balance. When running normal data
acquisition, OBOX dissipates about 45 W. If needed and if there is enough
power available from the station, heaters can be switched on to provide 20 W
to the internal side of the aluminum frame pocket. The thermal concept was
fully simulated using ABAQUS 6.10. To calibrate the simulations, some of the
thermal conduction paths were measured using mock-up models and with the first
test modules.

Each FEE dissipates 1 W. The power in a module is essentially dissipated by
the VA and the FPGA. To insure good thermal path, the VA is glued to a gold
pad on the PCB. This gold pad is connected through a large number of vias to
an internal copper plane in the middle of the PCB. This plane occupies the
full surface of the PCB. This central copper plane is in thermal contact with
the aluminum flange of the FEE which brings the heat to the top of the FEE. It
was found that the thermal transport can be enhanced by equipping the two
remaining sides of the PCB with a pyrolitic carbon foil (SIGMA_ALDRICH MERCK).
Those foils decrease the temperature gradient between the VA PCB and the top
of the FEE by several degrees.

The LV PS efficiency is overall 80% thanks to the usage of switching power
supplies. The 10W generated here are easily dissipated by the large PCB-to-
aluminum contact that the LV PS holder provides. A small dependency of the
total power consumption with temperature can be attributed to a degradation of
the efficiency with temperature. The HV PS additionally dissipates around 10 W
and again has ample contact between PCB holder and the aluminum frame. The CT
typically dissipates 5 W depending if it is idle or running the full data
acquisition. Each FPGA dissipates about 1.5 W which are evacuated by the
contact to the PCB. This PCB has a full layer devoted to thermal conduction.
The rest of the power is dissipated by the LVDS converters.

All the heat that is not dissipated through the paint is conducted to the rim
of the aluminum frame. The connection of the aluminum to Tiangong 2 using the
shock dampers is not very efficient in terms of heat transfer. Four flexible
cooling plates made of copper enhance the thermal connection and don’t
interfere with the vibration damping.

##  12 Basic performance parameters during first orbits of operation

The pre-orbit performances compared with the Monte Carlo were addressed in
another paper [5]. The full in-orbit performances and operation will be
addressed in a future paper [3]. We display here some essential parameters of
the detector that show that it performs as expected in space.
Figure 6 shows that the intrinsic noise of the instrument did not change
dramatically after the launch. As explained in [5], the noise of the
instrument consists of two parts: a correlated noise (shared by all bars of
the same module) and an intrinsic noise. The correlated noise is about three
time larger than the intrinsic noise but it can be measured event by event and
subtracted. A couple of bars became noisier and could be excluded from
analysis without significantly affecting the instrument performance.
Figure 7 shows that the gain of the instrument did not change after the
launch. The correlation is not 1 to 1 because the temperature in orbit is not
identical to the one on the launch pad. Some outliers are due to Compton edge
fitting not converging because of the low statistics collected on the launch
pad.
Figure 8 and 9 show the mean rate of raw events and cosmic ray triggers as a
function of the longitude and latitude. Rate of events is the rate of any
event that passes at least a single bar threshold. Cosmic rays trigger are
events with more then 8 bars passing the threshold.

The SAA and the polar cap region are clearly visible. The SAA induces a dead
time of the instrument of less then 10%. Due to failure of commanding during a
couple of orbits, we do have some rate measurements inside the SAA.
Figure 10 shows five random days of temperature measurements. What is shown is
the mean temperature of all modules versus time. Temperature is driven by the
solar irradiation that depends on the orbit and on the attitude of the
spacecraft. The fast temperature variation is due to the 90 minutes orbit. The
slow variation is due to attitude and season changes. The measured time
profile correspond well with our thermal simulations.

Figure 6: Intrinsic noise difference (difference between in orbit and at the
launch pad) distribution. In orbit our intrinsic noise is 0.4 ADC higher then
on the pad. Figure 7: ADC location of the 22Na Compton Edge before and after
the launch for the same High Voltage. The fitted line is forced to pass
through the origin. It has a slope of 1.18. The slope is different than 1
because the data on Earth was taken at a temperature twenty degree higher than
in space, compatible with the measured mean of -1% gain change by degree.
Figure 8: Rate of raw event trigger in Hz Figure 9: Cosmic raw trigger rate in
Hz Figure 10: Mean temperature of all modules versus UNIX time.

##  13 Conclusions

The flight model and the flight spare were sent to China and accepted for
flight during Summer 2016. The flight model was installed on the Tiangong 2
space laboratory in August 2016. POLAR together with Tiangong 2 where launched
into space by a Long March 2F rocket on September 15 2016 at 14:04 UTC.

POLAR was successfully switched on and gave immediately satisfactory results.
The thermal behavior was as expected. Using the heaters, the modules of OBOX
can be maintained within 5∘ around a mean temperature of 30∘.

At the time of writing POLAR has already seen several tens of GRB and some of
them are suitable for a polarization measurement. In-flight performance and
scientific results will be published elsewhere.

##  14 Funding

Funding:This work was supported by the National Natural Science Foundation of
China [grant number 11503028]; Swiss National Science Foundation; Swiss Space
Office [ESA PRODEX program]; National Science Center Poland [grants
2015/17/N/ST9/03556].

## References

## References

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∎

11institutetext: Beihang University22institutetext: 22email:
<EMAIL_ADDRESS>33institutetext: Beijing, 100191, China 44institutetext:
Carnegie Mellon University 66institutetext: Nankai University

# Non-pooling Network for medical image segmentation

Weihu Song  Heng Yu  Jianhua Wu

(Received: date / Accepted: date)

###### Abstract

Existing studies tend to focus on model modifications and integration with
higher accuracy, which improve performance but also carry huge computational
costs, resulting in longer detection times. In medical imaging, the use of
time is extremely sensitive. And at present most of the semantic segmentation
models have encoder-decoder structure or double branch structure. Their
several times of the pooling use with high-level semantic information
extraction operation cause information loss although there is a reverse
pooling or other similar action to restore information loss of pooling
operation. In addition, we notice that visual attention mechanism has superior
performance on a variety of tasks. Given this, this paper proposes non-pooling
network(NPNet), non-pooling commendably reduces the loss of information and
attention enhancement module effectively increases the weight of useful
information. The method greatly reduces the number of parameters and
computation costs by the shallow neural network structure. We evaluate the
semantic segmentation model of our NPNet on three benchmark datasets comparing
with multiple current state-of-the-art(SOTA) models, and the implementation
results show that our NPNet achieves SOTA performance, with an excellent
balance between accuracy and speed.

###### Keywords:

medical image segmentation non-pooling deep learning attention enhancement
module

##  1 Introduction

Medical image segmentation can promote the research and development of medical
field. It can help doctors analyse and take action using image features. The
accuracy and speed of image segmentation is critical and existing research is
carried out from these two aspects. However, the relationship between accuracy
and speed in most models has not reached a relative balance. FCNShelhamer et
al. (2017), as the first semantic segmentation model, undoubtedly attracted
great attention. It changed the last full connection layer of the
classification network into convolution to achieve remarkable performance on
semantic segmentation. U-netRonneberger et al. (2015), the first segmentation
network proposed for medical images, is a typical encoder-decoder structure.
In U-net, skip connections are used to effectively integrate shallow spatial
information and deep semantic information, thus making up for the loss of
feature information caused by multiple pooling operations in the encoder
stage. Subsequently, a series of improved models based on U-net show up. More
complex feature extraction modules are used to extract as much feature
information as possible from each level of the segmentation network to weaken
the influence of pooling operations on information loss. Although such models
improve certain performance, However, more redundant information, even error
information, was introduced, and the model size and computation cost also
increased significantly, creating a certain burden. SegNetBadrinarayanan et
al. (2017) uses two classification networks as encoder and decoder
respectively and proposes to use max pool index to do up-sampling to better
restore the impact of pooling. PSPNetZhao et al. (2017) and DeePLab seriesChen
et al. (2015)Chen et al. (2017)Chen et al. (2018a)Chen et al. (2018b) both use
image classification networks as the backbone. The former proves the
effectiveness of extracting multi-size feature information by pyramid pooling
module for the first time, while the latter proposes to use dilated
convolution to obtain feature information of larger receptive field, using
dilated spatial pyramid pooling (ASPP) to obtain rich feature information of
multiple dimensions. In addition, the attention mechanism introduced from NLP
to computer vision has also shown its dazzling brilliance, among which
SENetJie et al. (2017) is undoubtedly the most important representative, its
excellent performance won the last imagenet champion. Some other semantically
segmented networks use dual branching structuresHan et al. (2020) to acquire
semantic information, spatial information, and cascade structuresCheng et al.
(2020) respectively. Above all, most of the semantic segmentation models have
encoder-decoder structure, use image classification network as the backbone,
and use the structure of the double branch or cascade structure. Pooling
operation used in these semantic segmentation models leads to information
loss. And the complex structure will also cause the burden of model and
calculation. In addition, dilated convolution, multi-dimensional feature
extraction, and attention mechanisms are proved to be effective. Therefore, we
elaborately designed a simple and novelty non-pooling network, which solves
the information loss caused by the pooling operation and uses improved ASPP
and a new plug-and-play attention mechanism module. Our contribution is in
four aspects: (1) We propose a new plug-and-play attention mechanism module,
which has better performance than the attention module in SENet. (2) We
propose an improved ASPP module and have better performance. (3) For the first
time, non-pooling semantic segmentation model with only 1/50 of the number of
model parameters and computation costs of U-net is proposed. (4) Our method
surpasses other state-of-the-art performance on three medical image
segmentation datasets.

##  2 Methodology

In this paper, we propose NPNet, a novel lightweight semantic segmentation
model for medical images. The network structure is described in Fig 1. It is
mainly composed of the basic block, attention enhancement module shown in Fig
1, and feature enhancement module. In this model, all the convolution
operations are 3x3 convolution kernel, followed by batch normalization(bn) and
ReLU. There are three basic blocks at the beginning of the network, and
attention enhancement module is added after each block, and a feature
enhancement module is implemented in the middle of the network. At the back of
the network, 1x1 convolution is used to output according to the classification
number and bi-linear interpolation is used to restore the original input size.
In this section, we will talk about these components in detail.

(a) NPNet

(b) attention enhancement module

Figure 1: Proposed NPNet architecture.

###  2.1 Basic block

The basic block first uses 3x3 convolution operation with stride equal to 2,
which is equivalent to the function of reducing image size and computation
achieved by the pooling operation of stride equal to 2. Moreover, the
convolution operation can also effectively deal with the loss of feature
information in pooling operation. Then, two 3x3 convolution operations with
stride equal to 1 are used to fully extract the feature information of this
layer, and also to obtain more abundant and useful feature information which
is conducive to the transmission of the information of the next layer. The
design of this basic block is to reduce the information loss and realize the
effective extraction of spatial feature information of images with different
sizes.

###  2.2 Attention enhancement module

Attention enhancement module is an attention module integrated with 1x1
convolution. First, the input image is transformed into a 1-dimensional matrix
by adaptive average pooling, and then the input dimension is transformed into
the input dimension divided by parameter reduction using 1x1 convolution. Like
SENet, we also use linear activation function ReLU and nonlinear activation
function Sigmoid successively. The difference is that we use 1X1 convolution
to replace the full connection layer. 1X1 convolution can effectively improve
the nonlinear characteristics and information interaction across channels,
better extracting useful information in feature information. Finally, the
nonlinear activation function Sigmoid is used on output and the result is
weighted by multiplying the original input to achieve channel adaptive
weighting. This module is used after each basic block to further strengthen
the weight of useful information between different channels, thus providing
better characteristic information for the following steps.

###  2.3 Feature enhancement module

The feature enhancement module is used after three basic blocks, and the image
size currently is 1/8 of the input size. This module is composed of four
dilated convolutions with the ratio of 1, 5, 15, 20, and two 1x1 convolutions.
The dilated convolution can obtain feature information from the large
receptive field without increasing the number of parameters, obtaining richer
semantic information. The input image is first output through four dilated
convolutions according to 1/2 of the number of output channels. Then the four
outputs are superimposed through concatenation, and the number of channels is
2 times the number of output channels. 1x1 convolution is used to achieve
dimension reduction, that is, the normal number of output channels is
obtained. At this point, the residual structure is introduced to concatenate
the result with the original input information to realize feature reuse.
Finally, 1x1 convolution is used for further dimension reduction.

##  3 Experiments and Results

###  3.1 Datasets

Lung Segmentation. Lung CT image segmentation is an important and initial step
in lung CT image analysis. This dataset comes from the Kaggle contest, Finding
and Measuring Lungs in CT data111https://www.kaggle.com/kmader/finding-lungs-
in-ct-data(luna for short). It consists of 267 2D images and is randomly split
into train set (80%) and test set (20%). Also, we use the original image
equally.
Skin Lesion Segmentation. Computer-aided automatic diagnosis of skin cancer is
an inevitable trend, and skin lesions segmentation as the first step is
urgent. The data set is from MICCAI 2018 Workshop - ISIC2018: Skin Lesion
Analysis Towards Melanoma DetectionCodella et al. (2019)Tschandl et al.
(2018)(skin for short). It contains 2594 images and is randomly split into
train set (80%) and test set (20%). For better model training and result
display, we resize all the original images to 224 × 224.
Polyp Segmentation. Accurate detection of colon polyps is of great
significance for the prevention of colon cancer. CVC-ClinicDBBernal et al.
(2015)(CVC for short) includes 612 colon polyp images. We use the original
size 384x288 of image and split it into train set(80%) and test set(20%).

###  3.2 Experimental Settings

For three benchmarks and multiple segmentation models, we set consistent
training parameters. we set epochs as 100 in the three data sets. We use a
learning rate(LR) equal to 1e-3 for Luna and Skin task and 1e-4 for CVC task.
In addition, we use batch size equal to 2 for luna and CVC task, and 4 for the
skin task. Cross entropy loss and Adam are used as loss function and
optimizer, respectively. All experiments run on the NVIDIA GeForce RTX 2080Ti
GPU with 12GB. Intersection over Union (IOU), dice coefficient and
computational complexity(MACs) are selected as the evaluation metrics in this
paper. We used these evaluation metrics for all datasets.

Table 1: Comparsion on CVC, skin and luna with seven models Dataset | Methods | IOU | Dice | Params(M) | MACs(G)
---|---|---|---|---|---
CVC | FCN8sShelhamer et al. (2017) | 0.6149 | 0.7249 | 14.72 | 33.89
| SegNetBadrinarayanan et al. (2017) | 0.7146 | 0.7933 | 29.44 | 67.67
| PSPNetZhao et al. (2017) | 0.7159 | 0.8045 | 17.5 | 133.23
| U-NetRonneberger et al. (2015) | 0.7439 | 0.8229 | 34.53 | 110.46
| Attention U-NetOktay et al. (2018) | 0.7334 | 0.8153 | 34.87 | 112.27
| U-Net++Zhou et al. (2018) | 0.7632 | 0.8356 | 36.63 | 233.88
| NPNet | 0.7766 | 0.8397 | 0.71 | 2.17
skin | FCN8s | 0.7828 | 0.8511 | 14.72 | 61.50
| SegNet | 0.7897 | 0.8558 | 29.44 | 30.71
| PSPNet | 0.8052 | 0.8708 | 17.5 | 60.45
| U-Net | 0.8086 | 0.8691 | 34.53 | 50.12
| Attention U-Net | 0.8028 | 0.8691 | 34.87 | 50.94
| U-Net++ | 0.7901 | 0.8588 | 36.63 | 106.11
| NPNet | 0.8170 | 0.8757 | 0.71 | 0.99
luna | FCN8s | 0.9741 | 0.9802 | 14.72 | 80.32
| SegNet | 0.9688 | 0.9789 | 39.76 | 160.41
| PSPNet | 0.9732 | 0.9823 | 34.88 | 315.87
| U-Net | 0.9749 | 0.9821 | 39.09 | 261.64
| Attention U-Net | 0.9698 | 0.9794 | 29.30 | 266.11
| U-Net++ | 0.9746 | 0.9831 | 36.23 | 554.37
| NPNet | 0.9785 | 0.9832 | 0.71 | 5.15

###  3.3 Experimental Results

Segmentation results. In this section, we presented qualitative results on
three data sets and compared with other SOTA semantic segmentation networks to
prove the superior performance of our NPNet. We set up the same parameters for
the same data set in different network models, and all models were trained
from scratch. Since U-net is still the baseline of many networks, we also
introduce several SOTA models based on U-net for comparison. Table 2 shows
that our model is superior to other SOTA models in terms of performance and is
1/50 of U-net in terms of model size and computation costs. In all the figures
demonstrating the qualitative results in Fig 2, the sequence are origin image,
FCN8s, SegNet, PSPNet, UNet, NPNet, mask, respectively. It can be found from
these figures that the model proposed can effectively reduce the loss of
information with our non-pooling module, so as to retain more details and
achieve better performance. Moreover, the model size and computation cost of
this paper are only 1/100 of U-net++.
Ablation Studies. The attention mechanism module in SENet plays an important
role, and many models insert this template into their models to achieve better
performance. Therefore, we conducted an experimental comparison on three data
sets of our proposed attention enhancement module. The difference between the
model size and the computation costs of these three models can be negligible,
the experimental results in Table 1 prove that our attention enhancement
module is better than SENet as a plug-and-play attention module.

Table 2: Evaluation of proposed attention enhancement module Dataset | Methods | Attention | IOU | Dice
---|---|---|---|---
CVC | NPNet | no | 0.7439 | 0.8157
| NPNet | senet | 0.7448 | 0.8186
| NPNet | cam | 0.7766 | 0.8397
luna | NPNet | no | 0.9758 | 0.9807
| NPNet | senet | 0.9772 | 0.9820
| NPNet | cam | 0.9785 | 0.9832
skin | NPNet | no | 0.8131 | 0.8742
| NPNet | senet | 0.8091 | 0.8709
| NPNet | cam | 0.8165 | 0.8766

(a) CVC

(b) luna

(C) skin

Figure 2: Qualitative comparison of different segmentation results.

##  4 Conclusion

In this work, we propose a novel semantic segmentation network with non-
pooling operation for the first time, which can effectively alleviate the
problem of information loss and difficult recovery caused by the pooling
operation. Our proposed network also gets rid of common encoding and decoding
structures. In addition, we also proposed an attention module to enhance
feature information, which can be easily inserted into other network models
with fewer parameters, Experiment results on three datasets show that our
model can surpass state-of-art counterparts with lightweight parameters and
MACs.

## References

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