Counting of alpha particle tracks on imaging plate based on a convolutional neural network

Imaging plates are widely used to detect alpha particles to track information,and the number of alpha particle tracks is affected by the overlapping and fading effects of the track information.In this study,an experiment and a simulation were used to calibrate the efficiency parameter of an imaging plate,which was used to calculate the grayscale.Images were created by using grayscale,which trained the convolutional neural network to count the alpha tracks.The results demonstrated that the trained convolutional neural network can evaluate the alpha track counts based on the source and background images with a wider linear range,which was unaffected by the overlapping effect.The alpha track counts were unaffected by the fading effect within 60 min,where the calibrated formula for the fading effect was analyzed for 132.7 min.The detection efficiency of the trained convolutional neural network for inhomogeneous ^(241)Am sources(2π emission)was 0.6050±0.0399,whereas the efficiency curve of the photo-stimulated luminescence method was lower than that of the trained convolutional neural network.

A counting method for complex overlapping erythrocytes-based microscopic imaging

Red blood cell(RBC)counting is a standard medical test that can help diagnose various conditions and diseases.Manual counting of blood cells is highly tedious and time consuming.However,new methods for counting blood cells are customary employing both electronic and computer-assisted techniques.Image segmentation is a classical task in most image processing applications which can be used to count blood cells in a microscopic image.In this research work,an approach for erythrocytes counting is proposed.We employed a classification before counting and a new segmentation idea was implemented on the complex overlapping clusters in a microscopic smear image.Experimental results show that the proposed method is of higher counting accuracy and it performs much better than most counting algorithms existed in the situation of three or more RBCs overlapping complexly into a group.The average total erythrocytes counting accuracy of the proposed method reaches 92.9%.

Automatic counting method for complex overlapping erythrocytes based on seed prediction in microscopic imaging

Blood cell counting is an important medical test to help medical staffs diagnose various symptoms and diseascs.An automatic segmentation of complex overlapping erythrocytes based on seed prediction in microscopic imaging is proposed.The four main innovations of this ressearch are as.follows:(1)Regions of erythrocytes extracted rapidly and accurately based on the G component.(2)K-means algorithm is applied on edge detection of overlapping erythrocytes.(3)Traces of erythrocytes'biconcave shape are utilized to predict erythrocyte's position in overlapping clus-ters.(4)A new automatic counting method which aims at complex overlapping erythrocytes is presented.The experimental results show that the proposed method is efficient and accurate with very little running time.The average accuracy of the proposed method reaches 97.0%.

Spatially modulated scene illumination for intensity-compensated two-dimensional array photon-counting LiDAR imaging

Photon-counting LiDAR using a two-dimensional(2D)array detector has the advantages of high lateral resolution and fast acquisition speed.The non-uniform intensity profile of the illumination beam and non-uniform quantum efficiency of the detectors in the 2D array deteriorate the imaging quality.Herein,we propose a photon-counting LiDAR system that uses a spatial light modulator to control the spatial intensity to compensate for both the non-uniform intensity profile of the illumination beam,and the variation in the quantum efficiency of the detectors in the 2D array.By using a 635 nm peak wavelength and 4 mW average power semiconductor laser,lab-based experiments at a 4.27 m stand-off distance are performed to verify the effectiveness of the proposed method.Compared with the unmodulated method,the standard deviation of the intensity image of the proposed method is reduced from 0.109 to 0.089 for a whiteboard target,with an average signal photon number of 0.006 per pixel.

An FPGA-Based Pulse Pile-up Rejection Technique for Photon Counting Imaging Detectors

A novel FPGA-based pulse pile-up rejection method for single photon imaging detectors is reported. Tile method is easy to implement in FPGAs for real-time data processing. The rejection principle and entire design are introduced in detail. The photon counting imaging detector comprises a micro-channel plate （MCP） stack, and a wedge and strip anode （WSA）. The resolution mask pattern in front of the MCP can be reconstructed after data processing in the FPGA. For high count rates, the rejection design can effectively reduce the impact of the pulse pile-up on the image. The resolution can reach up to 140μm. The pulse pile-up rejection design can also be applied to high-energy physics and particle detection.

Automated Counting of Rice Planthoppers in Paddy Fields Based on Image Processing

A quantitative survey of rice planthoppers in paddy fields is important to assess the population density and make forecasting decisions. Manual rice planthopper survey methods in paddy fields are time-consuming, fatiguing and tedious. This paper describes a handheld device for easily capturing planthopper images on rice stems and an automatic method for counting rice planthoppers based on image processing. The handheld device consists of a digital camera with WiFi, a smartphone and an extrendable pole. The surveyor can use the smartphone to control the camera, which is fixed on the front of the pole by WiFi, and to photograph planthoppers on rice stems. For the counting of planthoppers on rice stems, we adopt three layers of detection that involve the following：（a） the first layer of detection is an AdaBoost classifier based on Haar features;（b） the second layer of detection is a support vector machine（SVM） classifier based on histogram of oriented gradient（HOG） features;（c） the third layer of detection is the threshold judgment of the three features. We use this method to detect and count whiteback planthoppers（Sogatella furcifera） on rice plant images and achieve an 85.2% detection rate and a 9.6% false detection rate. The method is easy, rapid and accurate for the assessment of the population density of rice planthoppers in paddy fields.

A new software for automated counting of glistenings in intraocular lenses in vivo

AIM:To assess the performance of a bespoke software for automated counting of intraocular lens(IOL)glistenings in slit-lamp images.METHODS:IOL glistenings from slit-lamp-derived digital images were counted manually and automatically by the bespoke software.The images of one randomly selected eye from each of 34 participants were used as a training set to determine the threshold setting that gave the best agreement between manual and automatic grading.A second set of 63 images,selected using randomised stratified sampling from 290 images,were used for software validation.The images were obtained using a previously described protocol.Software-derived automated glistenings counts were compared to manual counts produced by three ophthalmologists.RESULTS:A threshold value of 140 was determined that minimised the total deviation in the number of glistenings for the 34 images in the training set.Using this threshold value,only slight agreement was found between automated software counts and manual expert counts for the validating set of 63 images(κ=0.104,95%CI,0.040-0.168).Ten images(15.9%)had glistenings counts that agreed between the software and manual counting.There were 49 images(77.8%)where the software overestimated the number of glistenings.CONCLUSION:The low levels of agreement show between an initial release of software used to automatically count glistenings in in vivo slit-lamp images and manual counting indicates that this is a non-trivial application.Iterative improvement involving a dialogue between software developers and experienced ophthalmologists is required to optimise agreement.The results suggest that validation of software is necessary for studies involving semi-automatic evaluation of glistenings.

Modeling the photon counting and photoelectron counting characteristics of quanta image sensors

A signal chain model of single-bit and multi-bit quanta image sensors(QISs)is established.Based on the proposed model,the photoresponse characteristics and signal error rates of QISs are investigated,and the effects of bit depth,quantum efficiency,dark current,and read noise on them are analyzed.When the signal error rates towards photons and photoelectrons counting are lower than 0.01,the high accuracy photon and photoelectron counting exposure ranges are determined.Furthermore,an optimization method of integration time to ensure that the QIS works in these high accuracy exposure ranges is presented.The trade-offs between pixel area,the mean value of incident photons,and integration time under different illuminance level are analyzed.For the 3-bit QIS with 0.16 e-/s dark current and 0.21 e-r.m.s.read noise,when the illuminance level and pixel area are 1 lux and 1.21μm^(2),or 10000 lux and 0.21μm^(2),the recommended integration time is 8.8 to 30 ms,or 10 to21.3μs,respectively.The proposed method can guide the design and operation of single-bit and multi-bit QISs.

ASSESSMENT OF MYOCARDIAL VIABILITY WITH CONTRAST-ENHANCED MAGNETIC RESONANCE IMAGING AND COMPARISON WITH SINGLE-PHOTON EMISSION COMPUTED TOMOGRAPHY

Objective To compare contrast-enhanced magnetic resonance imaging （ceMRI） with nuclear metabolic imaging for the assessment of myocardial viability in patients with chronic ischemic heart disease. Methods Twenty patients with suspected chronic ischemic heart disease underwent ceMRI and technetium-99m sestamibi single-photon emission computed tomography （SPECT）. Patients with positive SPECT results also underwent 18 F-fluorodeoxyglucose （FDG） SPECT. In a 17-segment model, the segmental extent of hyperenhancement （SEH） by ceMRI was compared with segmental FDG and sestamibi uptake by SPECT. Correlation between the extent of hyperenhancement by ceMRI and left ventricular function was analyzed. Seven patients got negative results both in ceMRI and technetium-99m sestamibi SPECT. The rest 13 patients with positive results then underwent ^18F-FDG SPECT. In 221 segments of 13 patients, SEH was （2. 1±8.2）%, （25.0±13.7 ）%, and （57. 7±23.6 ）% in segments with normal metabolism/perfusion, metabolism/perfusion mismatch, and matched defects, respectively, and there were significant differences between either two of them （ all P 〈 0.05）. By receiver operating characteristic curve analysis, the area under the curve was 0. 95 for the differentiation between viable and non-viable segments. At the cutoff value of 34%, SEH optimally differentiated viable from non-viable segments defined by SPECT. Using this threshold, the sensitivity and specificity of ceMRI to detect non-viable myocardium as defined by SPECT were 92% and 93%, respectively. Hyperenhancement size by ceMRI was correlated negatively with the left ventricular ejection fraction （ r = - 0.90, P 〈 0.01 ） and positively with left ventricular volumes （ r = 0. 62 for end-diastolic volume, r = 0.75 for end-systolic volume, both P 〈 0.05 ）. Conclusion CeMRI allows assessment of myocardial viability with a high accuracy in patients with chronic ischemic heart disease.

High-resolution single-photon LiDAR without range ambiguity using hybrid-mode imaging [Invited]

We proposed a hybrid imaging scheme to estimate a high-resolution absolute depth map from low photon counts. It leverages measurements of photon arrival times from a single-photon LiDAR and an intensity image from a conventional high-resolution camera. Using a tailored fusion algorithm, we jointly processed the raw measurements from both sensors and output a high-resolution absolute depth map. We scaled up the resolution by a factor of 10, achieving 1300 × 2611 pixels and extending ~4.7 times the unambiguous range. These results demonstrated the superior capability of long-range high-resolution 3D imaging without range ambiguity.

Single-pixel 3D imaging based on fusion temporal data of single-photon detector and millimeter-wave radar

Recently,there has been increased attention toward 3D imaging using single-pixel single-photon detection(also known as temporal data)due to its potential advantages in terms of cost and power efficiency.However,to eliminate the symmetry blur in the reconstructed images,a fixed background is required.This paper proposes a fusion-data-based 3D imaging method that utilizes a single-pixel single-photon detector and millimeter-wave radar to capture temporal histograms of a scene from multiple perspectives.Subsequently,the 3D information can be reconstructed from the one-dimensional fusion temporal data by using an artificial neural network.Both the simulation and experimental results demonstrate that our fusion method effectively eliminates symmetry blur and improves the quality of the reconstructed images.

Photon-Counting Spectrometers Based on Superconducting Nanowire Single-Photon Detectors

Optical spectrum analysis provides a wealth of information about the physical world.Throughout the development of optical spectrum analysis,sensitivity has been one of the major topics and has become essential in applications dealing with faint light.Various high-sensitivity optical detection technologies have been applied in optical spectrum analysis to enhance its sensitivity to single-photon level.As an emerging single-photon detection technology,superconducting nanowire single-photon detectors(SNSPDs)have many impressive features such as high detection efficiency,broad operation bandwidth,small timing jitter,and so on,which make them promising for enhancing the performance of optical spectral analysis.Diverse schemes for photon-counting spectrometers based on SNSPDs have been demonstrated.This article reviews these impressive works and prospects for the future development of this technology.Further breakthroughs can be expected in its theories,device performance,applications,and combinations with in-sensor computing,promoting it to be a mature and versatile solution for optical spectrum analysis on ultra-faint light.

Fast fluorescence lifetime imaging techniques:A review on challenge and development

Fluorescence lifetime imaging microscopy(FLIM)is increasingly used in biomedicine,material science,chemistry,and other related research fields,because of its advantages of high specificity and sensitivity in monitoring cellular microenvironments,studying interaction between proteins,metabolic state,screening drugs and analyzing their efficacy,characterizing novel materials,and diagnosing early cancers.Understandably,there is a large interest in obtaining FLIM data within an acquisition time as short as possible.Consequently,there is currently a technology that advances towards faster and faster FLIM recording.However,the maximum speed of a recording technique is only part of the problerm.The acquisition time of a FLIM image is a complex function of many factors.These include the photon rate that can be obtained from the sample,the amount of information a technique extracts from the decay functions,the fficiency at which it determines fluorescence decay parameters from the recorded photons,the demands for the accuracy of these parameters,the number of pixels,and the lateral and axial resolutions that are obtained in biological materials.Starting from a discussion of the parameters which determine the acquisition time,this review will describe existing and emerging FLIM techniques and data analysis algo-rithms,and analyze their performance and recording speed in biological and biomedical applications.

Imaging properties of a tetra wedge readout

The decoding principle of a tetra wedge anode, which is a development of the wedge and strip anode, is described. The influence of charge cloud size on decoding accuracy is studied using the Monte Carlo method. Simulation results show that the decoding error is large when the size of charge clouds collected by the anode is small. Thus, the charge clouds collected by the tetra wedge anode should reach a necessary size to ensure accurate decoding. Finally, using the ultraviolet photon counting imaging system, the linearity and the spatial resolution of the system are tested. Experimental results show that the system has a good linearity and the spatial resolution is better than 100 μm.

Dark count in single-photon avalanche diodes:A novel statistical behavioral model

Dark count is one of the inherent noise types in single-photon diodes,which may restrict the performances of detectors based on these diodes.To formulate better designs for peripheral circuits of such diodes,an accurate statistical behavioral model of dark current must be established.Research has shown that there are four main mechanisms that contribute to the dark count in single-photon avalanche diodes.However,in the existing dark count models only three models have been considered,thus leading to inaccuracies in these models.To resolve these shortcomings,the dark current caused by carrier diffusion in the neutral region is deduced by multiplying the carrier detection probability with the carrier particle current at the boundary of the depletion layer.Thus,a comprehensive dark current model is constructed by adding the dark current caused by carrier diffusion to the dark current caused by the other three mechanisms.To the best of our knowledge,this is the first dark count simulation model into which incorporated simultaneously are the thermal generation,trap-assisted tunneling,band-to-band tunneling mechanisms,and carrier diffusion in neutral regions to evaluate dark count behavior.The comparison between the measured data and the simulation results from the models shows that the proposed model is more accurate than other existing models,and the maximum of accuracy increases up to 31.48%when excess bias voltage equals 3.5 V and temperature is 50℃.

Automatic counting of microglial cell activation and its applications

Glaucoma is a multifactorial optic neuropathy characterized by the damage and death of the retinal ganglion cells.This disease results in vision loss and blindness.Any vision loss resulting from the disease cannot be restored and nowadays there is no available cure for glaucoma; however an early detection and treatment,could offer neuronal protection and avoid later serious damages to the visual function.A full understanding of the etiology of the disease will still require the contribution of many scientific efforts.Glial activation has been observed in glaucoma,being microglial proliferation a hallmark in this neurodegenerative disease.A typical project studying these cellular changes involved in glaucoma often needs thousands of images- from several animals- covering different layers and regions of the retina.The gold standard to evaluate them is the manual count.This method requires a large amount of time from specialized personnel.It is a tedious process and prone to human error.We present here a new method to count microglial cells by using a computer algorithm.It counts in one hour the same number of images that a researcher counts in four weeks,with no loss of reliability.

Deep learning method for cell count from transmitted-light microscope

Automatic cell counting provides an effective tool for medical research and diagnosis.Currently,cell counting can be completed by transmitted-light microscope,however,it requires expert knowledge and the counting accuracy which is unsatisfied for overlapped cells.Further,the image-translation-based detection method has been proposed and the potential has been shown to accomplish cell counting from transmitted-light microscope,automatically and effectively.In this work,a new deep-learning(DL)-based two-stage detection method(cGAN-YOLO)is designed to further enhance the performance of cell counting,which is achieved by combining a DL-based fluorescent image translation model and a DL-based cell detection model.The various results show that cGAN-YOLO can effectively detect and count some different types of cells from the acquired transmitted-light microscope images.Compared with the previously reported YOLO-based one-stage detection method,high recognition accuracy(RA)is achieved by the cGAN-YOLO method,with an improvement of 29.80%.Furthermore,we can also observe that cGAN-YOLO obtains an improvement of 12.11%in RA compared with the previously reported image-translation-based detection method.In a word,cGAN-YOLO makes it possible to implement cell counting directly from the experimental acquired transmitted-light microscopy images with high flexibility and performance,which extends the applicability in clinical research.

On the Pollen Detection with Photoacoustic Imaging

A photoacoustic (PA) imaging that utilizes acoustic detection of sound generated by a specimen due to the absorption of modulated light was applied to measure the amount of the pollen of the Cryptomeria japonica, Asian allergic plant. High-sensitivity PA imaging can measure pollen particles with a large dynamic range from single particle to several hundred micrograms. The PA signal dependence on the amount of the pollen showed good correlation with the amount of pollen.

Fiber coupled high count-rate single-photon generated from InAs quantum dots

In this work,we achieve high count-rate single-photon output in single-mode(SM)optical fiber.Epitaxial and dilute InAs/GaAs quantum dots(QDs)are embedded in a GaAs/AlGaAs distributed Bragg reflector(DBR)with a micro-pillar cavity,so as to improve their light emission extraction in the vertical direction,thereby enhancing the optical SM fiber’s collection capabil-ity(numerical aperture:0.13).By tuning the temperature precisely to make the quantum dot exciton emission resonant to the micro-pillar cavity mode(Q~1800),we achieve a fiber-output single-photon count rate as high as 4.73×10^(6) counts per second,with the second-order auto-correlation g2(0)remaining at 0.08.

Analysis of Wide-Bandgap Material OPFET UV Detectors for High Dynamic Range Imaging and Communication Applications

The ultraviolet (UV) photoresponses of Wurtzite GaN, ZnO, and 6H-SiC-based Optical Field Effect Transistor (OPFET) detectors are estimated with an in-depth analysis of the same considering the generalized model and the front-illuminated model for high resolution imaging and UV communication applications. The gate materials considered for the proposed study are gold (Au) and Indium-Tin-Oxide (ITO) for GaN, Au for SiC, and Au and silver dioxide (AgO2) for ZnO. The results indicate significant improvement in the Linear Dynamic Range (LDR) over the previously investigated GaN OPFET (buried-gate, front-illuminated and generalized) models with Au gate. The generalized model has superior dynamic range than the front-illuminated model. In terms of responsivity, all the models including buried-gate OPFET exhibit high and comparable photoresponses. Buried-gate devices on the whole, exhibit faster response than the surface gate models except in the AgO2-ZnO generalized OPFET model wherein the switching time is the lowest. The generalized model enables faster switching than the front-illuminated model. The switching times in all the cases are of the order of nanoseconds to picoseconds. The SiC generalized OPFET model shows the highest 3-dB bandwidths of 11.88 GHz, 36.2 GHz, and 364 GHz, and modest unity-gain cut-off frequencies of 4.62 GHz, 8.71 GHz, and 5.71 GHz at the optical power densities of 0.575 μW/cm2, 0.575 mW/cm2, and 0.575 W/cm2 respectively. These are in overall, the highest detection-cum-amplifi-cation bandwidths among all the investigated devices. The same device exhibits the highest LDR of 73.3 dB. The device performance is superior to most of the other existing detectors along with comparable LDR, thus, emerging as a high performance photodetector for imaging and communication applications. All the detectors show considerably high detectivities owing to the high responsivity values. The results have been analyzed by the photovoltaic and the photoconductive effects, and the series resistance effects and will aid in conducting further research. The results are in line with the experiments and the commercially available software simulations. The devices will greatly contribute towards single photon counting, high resolution imaging, and UV communication applications.