CMOS Image Research Articles

High Total Ionizing Dose Effects on Backside-Illuminated CMOS Image Sensors

High Total Ionizing Dose Effects on Backside-Illuminated CMOS Image Sensors

Analysis for the Influence of Pixel Structure in Backside Illuminated CMOS Image Sensor

Analysis for the Influence of Pixel Structure in Backside Illuminated CMOS Image Sensor

Toward a Wireless Image Sensor for Real-Time Fluorescence Microscopy in Cancer Therapy.

We present a mm-sized, ultrasonically powered lensless CMOS image sensor as a progress towards wireless fluorescence microscopy. Access to biological information within the tissue has the potential to provide insights guiding diagnosis and treatment across numerous medical conditions including cancer therapy. This information, in conjunction with current clinical imaging techniques that have limitations in obtaining images continuously and lack wireless compatibility, can improve continual detection of multicell clusters deep within tissue. The proposed platform incorporates a 2.4 × 4.7 mm2 integrated circuit (IC) fabricated in TSMC 0.18 µm, a micro laser diode (µLD), a single piezoceramic and off-chip storage capacitors. The IC consists of a 36 × 40 array of capacitive trans-impedance amplifier-based pixels, wireless power management and communication via ultrasound and a laser driver all controlled by a Finite State Machine. The piezoceramic harvests energy from the acoustic waves at a depth of 2 cm to power up the IC and transfer 11.5 kbits/frame via backscattering. During Charge-Up, the off-chip capacitor stores charge to later supply a high-power 78 mW µLD during Imaging. Proof of concept of the imaging front end is shown by imaging distributions of CD8 T-cells, an indicator of the immune response to cancer, ex vivo, in the lymph nodes of a functional immune system (BL6 mice) against colorectal cancer consistent with the results of a fluorescence microscope. The overall system performance is verified by detecting 140 µm features on a USAF resolution target with 32 ms exposure time and 389 ms ultrasound backscattering.

Invited Paper] A High SNR Global Shutter CMOS Image Sensor Technology for High Precision Absorption Imaging Applications

Invited Paper] A High SNR Global Shutter CMOS Image Sensor Technology for High Precision Absorption Imaging Applications

Experiment and Analysis of Damage Effect of Proton Irradiation on Transmission Transistor of CMOS Image Sensor

Experiment and Analysis of Damage Effect of Proton Irradiation on Transmission Transistor of CMOS Image Sensor

A Back-Illuminated SPAD Fabricated With 40 nm CMOS Image Sensor Technology Achieving Near 40% PDP at 940 nm

A Back-Illuminated SPAD Fabricated With 40 nm CMOS Image Sensor Technology Achieving Near 40% PDP at 940 nm

BLEscope: A Bluetooth Low Energy (BLE) Microscope for Wireless Multicontrast Functional Imaging.

Recent advances in low-power wireless-capable system-on-chips (SoCs) have accelerated diverse Internet of Things (IoT) applications, encompassing wearables, asset monitoring, and more. Concurrently, the field of neuroimaging has experienced escalating demand for lightweight, untethered, low-power systems capable of imaging in small animals. This article explores the feasibility of using a low-power asset monitoring system as the basis of a new architecture for fluorescence and hemodynamic contrast-based wireless functional imaging. The core system architecture hinges on the fusion of a Bluetooth Low Energy (BLE) 5.2 SoC and a low-power 560×560, 8-bit monochrome CMOS image sensor module. Successful integration of a multicontrast optical front-end consisting of a fluorescence channel (FL) and an intrinsic optical signal (IOS) channel resulted in the creation of a wireless microscope called 'BLEscope'. Next, we developed a wireless (i.e. BLE) protocol to remotely operate the BLEscope via a laptop and acquire in vivo images at 1 frame per second (fps). We then conducted a comprehensive characterization of the BLEscope to assess its optical capabilities and power consumption. We report a new benchmark for continuous wireless imaging of ∼1.5 hours with a 100 mAh battery. Via the FL channel of the BLEscope, we successfully tracked the kinetics of an intravenously injected fluorescent tracer and acquired images of fluorescent brain tumor cells in vivo. Via the IOS channel, we characterized the differential response of normal and tumor-associated blood vessels to a carbogen gas inhalation challenge. When miniaturized, the BLEscope will result in a new class of low-power, implantable or wireless microscopes that could transform preclinical and clinical neuroimaging applications.

Design and Thermal Analysis of 2.5D and 3-D Integrated System of a CMOS Image Sensor and a Sparsity-Aware Accelerator for Autonomous Driving

Design and Thermal Analysis of 2.5D and 3-D Integrated System of a CMOS Image Sensor and a Sparsity-Aware Accelerator for Autonomous Driving

Data handling of CYGNO experiment using INFN-Cloud solution

The INFN Cloud project was launched at the beginning of 2020, aiming to build a distributed Cloud infrastructure and provide advanced services for the INFN scientific communities. A Platform as a Service (PaaS) was created inside INFN Cloud that allows the experiments to develop and access resources as a Software as a Service (SaaS), and CYGNO is the betatester of this system. The aim of the CYGNO experiment is to realize a large gaseous Time Projection Chamber based on the optical readout of the photons produced in the avalanche multiplication of ionization electrons in a GEM stack. To this extent, CYGNO exploits the progress in commercial scientific Active Pixel Sensors based on Scientific CMOS for Dark Matter search and Solar Neutrino studies. CYGNO, like many other astroparticle experiments, requires a computing model to acquire, store, simulate and analyze data typically far from High Energy Physics (HEP) experiments. Indeed, astroparticle experiments are typically characterized by being less demanding of computing resources with respect to HEP ones but have to deal with unique and unrepeatable data, sometimes collected in extreme conditions, with extensive use of templates and montecarlo, and are often re-calibrated and reconstructed many times for a given data set. Moreover, the varieties and the scale of computing models and requirements are extremely large. In this scenario, the Cloud infrastructure with standardized and optimized services offered to the scientific community could be a useful solution able to match the requirements of many small/medium size experiments. In this work, we will present the CYGNO computing model based on the INFN cloud infrastructure where the experiment software, easily extendible to similar experiments to similar applications on other similar experiments, provides tools as a service to store, archive, analyze, and simulate data.

Novel silicon detectors in ALICE at the LHC: The ITS3 and ALICE 3 upgrades

The ALICE experiment is preparing for the ITS3 upgrade, which is set to take place during the LHC Long Shutdown 3. The aim of this upgrade is to replace the three innermost tracking layers with truly cylindrical wafer-scale Monolithic Active Pixel Sensors (MAPS). By adopting this innovative technology, ALICE will further reduce the material budget and the distance from the interaction point, thus significantly improving its tracking and vertexing capabilities. The R&D program for ITS3 includes several advancements, such as operability of bent MAPS, validation of the 65 nm CMOS technology, and employment of the stitching process to produce wafer-scale sensors. In addition to the ITS3 upgrade, ALICE is designing a completely new apparatus, ALICE 3, planned for LHC Runs 5 and 6. The detector consists of a large MAPS-based tracking system covering eight units of pseudorapidity, complemented by multiple systems for particle identification, including silicon time-of-flight layers, a ring-imaging Cherenkov detector, a muon identification system, and an electromagnetic calorimeter. The vertex detector is based on an evolution of the ITS3 concept aiming at a track pointing resolution of better than 10 μm for tranverse momenta above 200 MeV/c through the integration of the tracking layers in a retractable structure inside the beam pipe. In this proceeding the detector concept of these upgrades is described, together with their physics motivations and R&D status and achievements.

High-speed 1-D and 2-D Raman scattering measurement for quantitative characterization of transient hydrogen jets

This paper reports the first quantitative characterization of transient hydrogen (H2) jets issued from a single-hole injector into nitrogen (N2), using high-speed 1-D and 2-D Raman scattering techniques. By employing the pulse-burst laser as the light source together with the low-noise EMCCD cameras running in subframe burst gating mode for signal collection, single-shot 1-D mole fraction of H2 (xH2) deduced from the ratio of H2 and N2 Raman scattering intensities, is obtained at repetition rate of 50 kHz. By changing the injection conditions, transient jet behaviors of both subsonic and highly under-expanded jets are well captured in single shots of 1-D, and the dynamic of the oblique shocks is visualized by local peaks in relative H2 number density. Statistical information regarding the jet behaviors is also obtained by repeating the measurement at same injection conditions, and the mixing between H2 and N2 can be directly evaluated by the average xH2. A coefficient of variance (COV) of 1.6 to 6 % is measured for all the conditions near the core region of the jets at late injection time, which demonstrates a good repeatability of the 1-D line measurements during the quasi-steady injection period. Using high-speed CMOS cameras, 2-D Raman imaging of transient H2 jets is performed at repetition rate of 10 kHz. Results in single shots demonstrate the vortices formation at the start of injection leading to turbulent mixing layers at later stages. Due to the low SNR, the accuracy and precision of the 2-D measurements is limited, and a one-to-one comparison of statistical results shows a maximum deviation of approximately 15 % from the more accurate 1-D measurements.

An affordable optical detection scheme for LSPR sensors

Biosensing technologies are essential for advancing healthcare by enabling rapid point-of-care (POC) testing and diagnosis, potentially saving lives. Biosensors, such as Localized Surface Plasmon Resonance (LSPR) sensors with gold nanoparticles (AuNPs), show promise in early disease diagnosis due to their simple structure and high sensitivity. However, their commercialization is limited by high production costs and the need for precise optoelectronic systems. This article proposes an affordable optical detection scheme for LSPR sensors named BioColor. BioColor uses a color CMOS camera to capture images of light passing through the sensor elements, which are plasmonic papers composed of AuNPs. Variations in the refractive index over the sensor’s surface cause changes in the color of the transmitted light. This color change can be detected through image processing algorithms and the detection results are visualized on the BioColor mobile app, providing instant automated access to sensing outcomes.

Experimental astronomical observation using a lobster eye optics

AbstractA lobster eye (LE) is a wide‐field type of X‐ray optics, which provides a large field of view at the expense of angular resolution. The optics presented in this paper are the LE optics in Schmidt arrangement made from glass sheets with golden reflective coatings. It was used as a scientific payload on the WRXR rocket experiment. Before the mission itself, the optics was tested on ground to obtain more information about its behavior. Part of these tests were several nights of observation at the Ondrejov observatory. We used the optics in combination with a CMOS camera to acquire images in visible light of various bright sources in the sky. In order to enable long‐time exposures, the robotic mount of the BART telescope was used. The goal of this experiment was to confirm the focal length of the optics using a source at infinity, and to show how the optics, designed for X‐ray observations, performs in visible light. This brief article describes the methods used for evaluation and presents and discusses the results obtained within the night observation experiment.

A Biomimetic Visual Detection Model: Event-Driven LGMDs Implemented With Fractional Spiking Neuron Circuits.

Lobula giant motion detectors (LGMDs) in locusts effectively predict collisions and trigger avoidance, with potential applications in autonomous driving and UAVs. Research on LGMD characteristics splits into two views: one focusing on the presynaptic visual pathway, the other on the postsynaptic LGMD neurons. Both perspectives have support, leading to two computational models, but they lack a biophysical description of the individual LGMD neuron behavior. This paper aims to mimic and explain LGMD behavior based on fractional spiking neurons (FSNs) and construct a biomimetic visual model for the LGMD compatible with these characteristics. We implement the visual model using an event camera to simulate photoreceptors and follow the ON/OFF visual pathway, incorporating lateral inhibition to mimic the LGMD system from the bottom up. Second, most computational models of motion perception use only the dendrites within the LGMD neurons as the ideal pathway for linear summation, ignoring dendritic effects inducing neuronal properties. Thus, we introduce FSN circuits by altering dendritic morphological parameters to simulate multi-scale spike frequency adaptation (SFA) observed in LGMDs. Additionally, we add one more circuit of dendritic trees into the FSNs to be compatible with the postsynaptic feed-forward inhibition (FFI) in LGMD neurons, providing a novel explanatory and predictive model. We test that the event-driven biomimetic visual model can achieve collision detection and looming selection in different complex scenes, especially fast-moving objects.

Alpha Particle-Induced Persistent Effects in a COTS 3D-Integrated CMOS Imager

Alpha Particle-Induced Persistent Effects in a COTS 3D-Integrated CMOS Imager

Viabilidade do uso de drone aplicado no mapeamento da pesca artesanal comercial: um estudo de caso na Baía de Sepetiba, Rio de Janeiro

ABSTRACT: This article presents an experimental study to verify the feasibility of using the emerging UAV technology in the mapping of fishing grounds exploited by artisanal fishing in Sepetiba Bay, in the south of the state of Rio de Janeiro-Brazil, aiming to better understand the functionality and information generated by the equipment, and whether the data can help improve local fisheries management and also provide information for the implementation of simplified traceability for regional fish. The study area included four locations, Ilha da Madeira, Vila Geny, Coroa Grande and Ponte Preta, all located in Sepetiba Bay, located in the municipality of Itaguaí, in the southern region of the state of Rio de Janeiro. The aerial mapping was carried out in September, October and November 2017, between 10 am and 12 pm (GMT-3), employing a Phantom 3 Professional UAV (DJI, Shenzhen, China), Anac Brasil registration number PP-011092014. The onboard camera a DJI 4K Edition Sony Exmor R Model IMX117: 7.81mm equipped with a CMOS sensor dimension of 6.2 mm, 4000 x 3000 12 megapixel resolution, with an f/2.8 lens and field of view (FOV) of 94, having a focal length of 14mm. Images were collected perpendicularly to the main plan. Flight height was set at 80 m, flight speed was determined based on the overlap of 80%, dimension of area to be mapped, and battery life. Hence, the operator utilized a average flight speed of 25 km/h. ground sample distance (GSD) was 1.20 cm/px. and an overlap of 80% between images was established to avoid possible failures and orthomosaic information gaps. For each fishery mapped, standard software processing was carried out, which consists of: aligning the photos, creating a point cloud, creating a digital elevation model, and finally the orthomosaic itself. Once processed, the orthomosaics were exported from Agis Soft Photo Scan Professional to Google Earth (Google Inc.), where it is possible to make a more comprehensive assessment of fisheries in a much more practical and faster way. A total of four flights were carried out, one for each study area, averaging 10 minutes each. As a result, the technology proved to be viable to apply, since it made it possible to identify and map the areas defined for this research, generating data such as distance and, characteristics of the place, which could be used to track the fish caught and landed, in addition to enabling the monitoring of vessels and fishing, and thus improve the management of local fisheries.

High Precision Ping-Pong Auto-Zeroed Lock-in Fluorescence Photometry Sensor.

This paper presents a high-precision CMOS fluorescence photometry sensor using a novel lock-in amplification scheme based on switched-biasing and ping-pong auto-zeroing techniques. The CMOS sensor includes two photodiodes and a lock-in amplifier (LIA) operating at 1 kHz. The LIA comprises a differential low-noise amplifier using a novel switched-biasing ping-pong auto-zeroed scheme, an automatic phase aligner, a programmable gain amplifier, a band-pass filter, a mixer, and an output low-pass filter. The design is fabricated in 0.18-µm CMOS process, and the measurement shows that the LIA can retrieve noisy input signals with a dynamic reserve of 42 dB, while consuming only 0.7 mW from a 1.8 V supply voltage. The measured results show that the LIA can detect a wide range of incident light power from 8 nW to 24 µW. The proposed design is encapsulated in a 3D-printed housing allowing for real-time invitro biomarker detection. This ambulatory platform uses an LED and a fiber optic to convey the excitation light to the sample and retrieve the fluorescence signal. Experiments with a beads solution diluted in PBS demonstrate that the sensor has a sensitivity of 1:100 k. Experimental results obtained invitro with NIH3T3 mouse cells tagged with membrane dye show the ability of the prototype to detect different densities of cell culture. The portable prototype, which includes optical filters and a small 30 mm × 36 mm × 30 mm printed circuit board enclosed inside the 3D-printed housing, consumes 36.7 mW and weighs 120 g.

Upgrade of Belle II vertex detector with CMOS pixel technology

The Belle II experiment at KEK in Japan considers upgrading its vertex detector system to address the challenges posed by high background levels caused by the increased luminosity of the SuperKEKB collider. One proposal for upgrading the vertex detector aims to install a 5-layer all monolithic pixel vertex detector based on fully depleted CMOS sensors in 2027. The new system will use the OBELIX MAPS chips to improve background robustness and reduce occupancy levels through small and fast pixels. This causes better track finding, especially for low transverse momenta tracks. This text will focus on the predecessor of the OBELIX sensor, the TJ-Monopix2, presenting laboratory and test beam results on pixel response, efficiency, and spatial resolution.

Wavelength-scanning pixel-super-resolved lens-free on-chip quantitative phase microscopy with a color image sensor

We report a wavelength-scanning-based lens-free on-chip microscope using a color CMOS sensor and a matching modified phase retrieval algorithm for pixel super-resolution. Compared to traditional monochrome industrial cameras, color sensors favored by the consumer electronics industry have smaller pixel sizes, higher performance, and lower costs. However, the color filtering array (CFA) introduces inherent modulation to the holograms acquired under quasi-monochromatic illumination, which complicates the data processing in lens-free on-chip microscopy. Without physically removing the CFA positioned on the sensor chip, we demonstrate quantitative phase imaging (QPI) with a lateral half-width resolution of 615 nm over a wide field-of-view of 51.88 mm2 by exploiting the green-channel data from Bayer-masked holograms. The resulting spatial bandwidth product is 137.2 megapixels, over 10 times that of a conventional optical microscope. The rationale for using only green-channel data is that the information from each sampling point is not lost during propagation but rather distributed to all pixels in the image. Therefore, the missing data in other channels can be recovered by exploiting the sufficient differences among the raw images captured at different wavelengths. Compared to the scheme with monochrome sensors, this method requires the acquisition of several more images to guarantee the convergence of the algorithm. Experimental results show that we can achieve high-quality QPI performance, thus demonstrating the applicability of cost-effective color sensors in the field of lens-free holographic microscopy.

Research on the design of automatic image processing function for intelligent face management system

Abstract Around the background of rapid development of intelligent technology, an efficient image processing system oriented to the smart management of human faces is focused on. The system is mainly developed towards high speed, high definition, high integration and reliability. The article investigates a novel automatic image processing algorithm, covering three key modules: automatic exposure control, color interpolation and chromaticity space conversion. The algorithm can process the output image of CMOS sensor in Bayer format in real time and adjust the image parameters to obtain a high-quality image. In terms of face recognition performance, the algorithm has a significant advantage in recognition speed compared with other algorithms, and the average recognition accuracy reaches 94.258%. In the practical application of ID card portrait processing, the image shows a more uniform grayscale distribution in the range of 5 to 255 after automatic color adjustment, and the color quality is significantly improved. Meanwhile, in the portrait enhancement experiments, the images obtained with this image automatic processing algorithm outperform the traditional ID card image processing methods regarding information entropy, mutual information, standard deviation and peak signal-to-noise ratio (PSNR).