scholarly journals Human Body-Related Disease Diagnosis Systems Using CMOS Image Sensors: A Systematic Review

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2098
Author(s):  
Suparshya Babu Sukhavasi ◽  
Susrutha Babu Sukhavasi ◽  
Khaled Elleithy ◽  
Shakour Abuzneid ◽  
Abdelrahman Elleithy
Keyword(s):  
Systematic Review ◽  
Life Expectancy ◽  
Human Body ◽  
Human Life ◽  
Disease Diagnosis ◽  
Image Sensor ◽  
Image Sensors ◽  
Average Life Expectancy ◽  
Cmos Image Sensors ◽  
Control And Prevention

According to the Center for Disease Control and Prevention (CDC), the average human life expectancy is 78.8 years. Specifically, 3.2 million deaths are reported yearly due to heart disease, cancer, Alzheimer’s disease, diabetes, and COVID-19. Diagnosing the disease is mandatory in the current way of living to avoid unfortunate deaths and maintain average life expectancy. CMOS image sensor (CIS) became a prominent technology in assisting the monitoring and clinical diagnosis devices to treat diseases in the medical domain. To address the significance of CMOS image ‘sensors’ usage in disease diagnosis systems, this paper focuses on the CIS incorporated disease diagnosis systems related to vital organs of the human body like the heart, lungs, brain, eyes, intestines, bones, skin, blood, and bacteria cells causing diseases. This literature survey’s main objective is to evaluate the ‘systems’ capabilities and highlight the most potent ones with advantages, disadvantages, and accuracy, that are used in disease diagnosis. This systematic review used PRISMA workflow for study selection methodology, and the parameter-based evaluation is performed on disease diagnosis systems related to the human body’s organs. The corresponding CIS models used in systems are mapped organ-wise, and the data collected over the last decade are tabulated.

scholarly journals 1/f Noise Modelling and Characterization for CMOS Quanta Image Sensors

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5459
Author(s):  
Wei Deng ◽  
Eric R. Fossum
Keyword(s):  
Analog Circuits ◽  
Image Sensor ◽  
Image Sensors ◽  
Correlated Double Sampling ◽  
Cmos Image Sensors ◽  
Source Follower ◽  
Cmos Analog Circuits ◽  
Different Origins ◽  
Noise Models ◽  
Fitting Model

This work fits the measured in-pixel source-follower noise in a CMOS Quanta Image Sensor (QIS) prototype chip using physics-based 1/f noise models, rather than the widely-used fitting model for analog designers. This paper discusses the different origins of 1/f noise in QIS devices and includes correlated double sampling (CDS). The modelling results based on the Hooge mobility fluctuation, which uses one adjustable parameter, match the experimental measurements, including the variation in noise from room temperature to –70 °C. This work provides useful information for the implementation of QIS in scientific applications and suggests that even lower read noise is attainable by further cooling and may be applicable to other CMOS analog circuits and CMOS image sensors.

scholarly journals Proximity Gettering Design of Hydrocarbon–Molecular–Ion–Implanted Silicon Wafers Using Dark Current Spectroscopy for CMOS Image Sensors

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2073 ◽  
Author(s):  
Kazunari Kurita ◽  
Takeshi Kadono ◽  
Satoshi Shigematsu ◽  
Ryo Hirose ◽  
Ryosuke Okuyama ◽  
...  
Keyword(s):  
Dark Current ◽  
Image Sensor ◽  
Image Sensors ◽  
Silicon Wafers ◽  
Device Fabrication ◽  
Oxide Semiconductor ◽  
Device Performance ◽  
Molecular Ion ◽  
Cmos Image Sensors ◽  
Ion Implanted

We developed silicon epitaxial wafers with high gettering capability by using hydrocarbon–molecular–ion implantation. These wafers also have the effect of hydrogen passivation on process-induced defects and a barrier to out-diffusion of oxygen of the Czochralski silicon (CZ) substrate bulk during Complementary metal-oxide-semiconductor (CMOS) device fabrication processes. We evaluated the electrical device performance of CMOS image sensor fabricated on this type of wafer by using dark current spectroscopy. We found fewer white spot defects compared with those of intrinsic gettering (IG) silicon wafers. We believe that these hydrocarbon–molecular–ion–implanted silicon epitaxial wafers will improve the device performance of CMOS image sensors.

scholarly journals Super Field-of-View Lensless Camera by Coded Image Sensors

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1329 ◽  
Author(s):  
Tomoya Nakamura ◽  
Keiichiro Kagawa ◽  
Shiho Torashima ◽  
Masahiro Yamaguchi
Keyword(s):  
Imaging System ◽  
Complementary Metal Oxide Semiconductor ◽  
Image Sensor ◽  
Image Sensors ◽  
Computational Imaging ◽  
Field Of View ◽  
Oxide Semiconductor ◽  
Back Side ◽  
Cmos Image Sensors ◽  
Rich Information

A lensless camera is an ultra-thin computational-imaging system. Existing lensless cameras are based on the axial arrangement of an image sensor and a coding mask, and therefore, the back side of the image sensor cannot be captured. In this paper, we propose a lensless camera with a novel design that can capture the front and back sides simultaneously. The proposed camera is composed of multiple coded image sensors, which are complementary-metal-oxide-semiconductor (CMOS) image sensors in which air holes are randomly made at some pixels by drilling processing. When the sensors are placed facing each other, the object-side sensor works as a coding mask and the other works as a sparsified image sensor. The captured image is a sparse coded image, which can be decoded computationally by using compressive sensing-based image reconstruction. We verified the feasibility of the proposed lensless camera by simulations and experiments. The proposed thin lensless camera realized super-field-of-view imaging without lenses or coding masks and therefore can be used for rich information sensing in confined spaces. This work also suggests a new direction in the design of CMOS image sensors in the era of computational imaging.

A 4-tap global shutter pixel with enhanced IR sensitivity for VGA time-of-flight CMOS image sensors

2020 ◽  
Vol 2020 (7) ◽  
pp. 103-1-103-6
Author(s):  
Taesub Jung ◽  
Yonghun Kwon ◽  
Sungyoung Seo ◽  
Min-Sun Keel ◽  
Changkeun Lee ◽  
...  
Keyword(s):  
Time Of Flight ◽  
Light Sensitivity ◽  
Image Sensor ◽  
Image Sensors ◽  
Double Sampling ◽  
Back Side ◽  
Long Distance ◽  
Correlated Double Sampling ◽  
Cmos Image Sensors ◽  
Side Illumination

An indirect time-of-flight (ToF) CMOS image sensor has been designed with 4-tap 7 μm global shutter pixel in back-side illumination process. 15000 e- of high full-well capacity (FWC) per a tap of 3.5 μm pitch and 3.6 e- of read-noise has been realized by employing true correlated double sampling (CDS) structure with storage gates (SGs). Noble characteristics such as 86 % of demodulation contrast (DC) at 100MHz operation, 37 % of higher quantum efficiency (QE) and lower parasitic light sensitivity (PLS) at 940 nm have been achieved. As a result, the proposed ToF sensor shows depth noise less than 0.3 % with 940 nm illuminator in even long distance.

scholarly journals The Sugars with the Potential to Prolong Human Life

2021 ◽  
Author(s):  
Tomoya Shintani ◽  
Laura Lema-Perez ◽  
Hideya Shintani
Keyword(s):  
Diabetes Mellitus ◽  
Insulin Resistance ◽  
Life Expectancy ◽  
Human Body ◽  
Human Life ◽  
Metabolic Process ◽  
The Other ◽  
Health Conditions ◽  
Sugar Intake ◽  
Excessive Intake

Sugar is the main source of energy for all cells in the human body. On the other hand, cells can also obtain energy from fats and proteins depending on conditions, although this metabolic process is more difficult and less common in cells. Sugar intake has increased in recent decades and is included in most of our dietary products. However, many studies indicate that sugar intake increases the prevalence of suffering from various harmful health conditions such as obesity. As a consequence, obesity is related to several chronic diseases such as hypertension, insulin resistance, and diabetes mellitus in humans. This is due to an excessive intake of sugars and sedentary lifestyles, causing a deterioration in the organs of our body, and consequently, reducing life expectancy. In this chapter, sugars that both shorten and lengthen life expectancy are presented. The latter are recent options that have emerged in order to continue sweetening our food in a healthier way, and would be new geroprotectors.

scholarly journals A CMOS voltage-mode image sensing system

2021 ◽  
Author(s):  
Jun Long Zhang
Keyword(s):  
Cmos Image Sensor ◽  
Cmos Technology ◽  
Image Sensor ◽  
Electrical Signal ◽  
Image Sensors ◽  
Analog To Digital ◽  
Light Sensing ◽  
Image Sensing ◽  
Cmos Image Sensors ◽  
Pixel Sensors

A CMOS image sensor consists of a light sensing region that converts photonic energy to an electrical signal and a peripheral circuitry that performs signal conditioning and post-processing. This project investgates the principle and design of CMOS active image sensors. The basic concepts and principle of CMOS image sensors are investigated. The advantages of CMOS image sensors over charge-coupled device (CCD) image sensors are presented. Both passive pixel sensors (PPS) and acive pixel sensors (APS) are examined in detail. The noise of CMOS image sensors is investigated and correlated double sampling (CDS) techniques are examined. The design of APS arrays, CDS circuits and 8-bit analog to-digital converters in TSMC-0.18μm 1.8V CMOS technology is presented. The simulation results and layout of the designed CMOS image sensor are presented.

Research on Driver Design for CMOS Image Sensor Based on DM642

2013 ◽  
Vol 321-324 ◽  
pp. 994-997
Author(s):  
Ping Xian Yang ◽  
Zhen Bao Liu ◽  
Tao Jin
Keyword(s):  
Fixed Point ◽  
Digital Signal Processor ◽  
Digital Signal ◽  
Image Sensor ◽  
Image Sensors ◽  
Video Capture ◽  
Sensor Interface ◽  
Cmos Image Sensors ◽  
Cmos Sensor ◽  
Different Levels

This paper mainly researches on the TI company fixed-point digital signal processor TMS320DM642 video capture technology for CMOS image sensors, sensor interface and video mini-driver carried out a detailed analysis, established different levels of peripheral structures under different CMOS Sensor, the research in this field has flexible characteristics and high practical value.

Deep Learning based Fruit Freshness Classification and Detection with CMOS Image sensors and Edge processors

2020 ◽  
Vol 2020 (12) ◽  
pp. 172-1-172-7 ◽  
Author(s):  
Tejaswini Ananthanarayana ◽  
Raymond Ptucha ◽  
Sean C. Kelly
Keyword(s):  
Deep Learning ◽  
Object Detection ◽  
Image Classification ◽  
High Speed ◽  
Image Sensor ◽  
Vital Role ◽  
Image Sensors ◽  
Classification Model ◽  
Detection Model ◽  
Cmos Image Sensors

CMOS Image sensors play a vital role in the exponentially growing field of Artificial Intelligence (AI). Applications like image classification, object detection and tracking are just some of the many problems now solved with the help of AI, and specifically deep learning. In this work, we target image classification to discern between six categories of fruits — fresh/ rotten apples, fresh/ rotten oranges, fresh/ rotten bananas. Using images captured from high speed CMOS sensors along with lightweight CNN architectures, we show the results on various edge platforms. Specifically, we show results using ON Semiconductor’s global-shutter based, 12MP, 90 frame per second image sensor (XGS-12), and ON Semiconductor’s 13 MP AR1335 image sensor feeding into MobileNetV2, implemented on NVIDIA Jetson platforms. In addition to using the data captured with these sensors, we utilize an open-source fruits dataset to increase the number of training images. For image classification, we train our model on approximately 30,000 RGB images from the six categories of fruits. The model achieves an accuracy of 97% on edge platforms using ON Semiconductor’s 13 MP camera with AR1335 sensor. In addition to the image classification model, work is currently in progress to improve the accuracy of object detection using SSD and SSDLite with MobileNetV2 as the feature extractor. In this paper, we show preliminary results on the object detection model for the same six categories of fruits.

Study on Image Sensor Controlling Circuit for Wireless Endoscopic MEMS

2012 ◽  
Vol 220-223 ◽  
pp. 1003-1007
Author(s):  
Ying Jun Chen ◽  
Zhong Hua Sun ◽  
Huang Ping
Keyword(s):  
Power Consumption ◽  
Human Body ◽  
Animal Experiments ◽  
Image Sensor ◽  
Small Dimension ◽  
Image Sensors ◽  
Working Environment ◽  
Low Power Consumption ◽  
Integration Density ◽  
Signal Output

In this paper the design and experiments of image sensor controlling circuit using in wireless endoscopic MEMS was studied. Through comparing the excellency and deficiency of various types of image sensors, and considering the working environment and requirements in the human body, it is pointed out that the CMOS image sensor with high integration density, low power consumption, small dimension and analog image signal output is suitable for the wireless endoscopic MEMS. By theoretically analyzing, the controlling circuits of two typical image sensors were designed successfully. The images captured in the animal experiments prove the validity of the designed circuits for the wireless endoscopic MEMS.

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