Human Body-Related Disease Diagnosis Systems Using CMOS Image Sensors: A Systematic Review
| Autor: | Abdelrahman Elleithy, Khaled M. Elleithy, Susrutha Babu Sukhavasi, Shakour Abuzneid, Suparshya Babu Sukhavasi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Diagnostic Imaging
medicine.medical_specialty Heart disease Coronavirus disease 2019 (COVID-19) implantable CMOS image sensors Review 02 engineering and technology Disease lcsh:Chemical technology 01 natural sciences Biochemistry CMOS image sensors Analytical Chemistry Diabetes mellitus medicine Humans lcsh:TP1-1185 Electrical and Electronic Engineering medical imaging systems Intensive care medicine Instrumentation Human Body biomedical CMOS image sensors business.industry medical applications 010401 analytical chemistry CMOS Human body 021001 nanoscience & nanotechnology medicine.disease Atomic and Molecular Physics and Optics 0104 chemical sciences smartphone CMOS image sensors Semiconductors Clinical diagnosis Life expectancy 0210 nano-technology business Literature survey |
| Zdroj: | Sensors, Vol 21, Iss 2098, p 2098 (2021) Sensors (Basel, Switzerland) |
| ISSN: | 1424-8220 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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