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

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...

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Main Authors: Suparshya Babu Sukhavasi, Susrutha Babu Sukhavasi, Khaled Elleithy, Shakour Abuzneid, Abdelrahman Elleithy
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/21/6/2098
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spelling doaj-13e10cd5a91c4f7a9bf49f1c6dd1974e2021-03-18T00:01:26ZengMDPI AGSensors1424-82202021-03-01212098209810.3390/s21062098Human Body-Related Disease Diagnosis Systems Using CMOS Image Sensors: A Systematic ReviewSuparshya Babu Sukhavasi0Susrutha Babu Sukhavasi1Khaled Elleithy2Shakour Abuzneid3Abdelrahman Elleithy4Department of Computer Science and Engineering, University of Bridgeport, Bridgeport, CT 06604, USADepartment of Computer Science and Engineering, University of Bridgeport, Bridgeport, CT 06604, USADepartment of Computer Science and Engineering, University of Bridgeport, Bridgeport, CT 06604, USADepartment of Computer Science and Engineering, University of Bridgeport, Bridgeport, CT 06604, USADepartment of Computer Science, William Paterson University, Wayne, NJ 07470, USAAccording 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.https://www.mdpi.com/1424-8220/21/6/2098CMOSCMOS image sensorsmedical imaging systemsmedical applicationsbiomedical CMOS image sensorsimplantable CMOS image sensors
collection DOAJ
language English
format Article
sources DOAJ
author Suparshya Babu Sukhavasi
Susrutha Babu Sukhavasi
Khaled Elleithy
Shakour Abuzneid
Abdelrahman Elleithy
spellingShingle Suparshya Babu Sukhavasi
Susrutha Babu Sukhavasi
Khaled Elleithy
Shakour Abuzneid
Abdelrahman Elleithy
Human Body-Related Disease Diagnosis Systems Using CMOS Image Sensors: A Systematic Review
Sensors
CMOS
CMOS image sensors
medical imaging systems
medical applications
biomedical CMOS image sensors
implantable CMOS image sensors
author_facet Suparshya Babu Sukhavasi
Susrutha Babu Sukhavasi
Khaled Elleithy
Shakour Abuzneid
Abdelrahman Elleithy
author_sort Suparshya Babu Sukhavasi
title Human Body-Related Disease Diagnosis Systems Using CMOS Image Sensors: A Systematic Review
title_short Human Body-Related Disease Diagnosis Systems Using CMOS Image Sensors: A Systematic Review
title_full Human Body-Related Disease Diagnosis Systems Using CMOS Image Sensors: A Systematic Review
title_fullStr Human Body-Related Disease Diagnosis Systems Using CMOS Image Sensors: A Systematic Review
title_full_unstemmed Human Body-Related Disease Diagnosis Systems Using CMOS Image Sensors: A Systematic Review
title_sort human body-related disease diagnosis systems using cmos image sensors: a systematic review
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2021-03-01
description 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.
topic CMOS
CMOS image sensors
medical imaging systems
medical applications
biomedical CMOS image sensors
implantable CMOS image sensors
url https://www.mdpi.com/1424-8220/21/6/2098
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