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...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-03-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/21/6/2098 |
id |
doaj-13e10cd5a91c4f7a9bf49f1c6dd1974e |
---|---|
record_format |
Article |
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 |
work_keys_str_mv |
AT suparshyababusukhavasi humanbodyrelateddiseasediagnosissystemsusingcmosimagesensorsasystematicreview AT susruthababusukhavasi humanbodyrelateddiseasediagnosissystemsusingcmosimagesensorsasystematicreview AT khaledelleithy humanbodyrelateddiseasediagnosissystemsusingcmosimagesensorsasystematicreview AT shakourabuzneid humanbodyrelateddiseasediagnosissystemsusingcmosimagesensorsasystematicreview AT abdelrahmanelleithy humanbodyrelateddiseasediagnosissystemsusingcmosimagesensorsasystematicreview |
_version_ |
1724218032925966336 |