| Title |
Recent Advancements of Computer Vision in Healthcare: A Systematic Review |
| Authors |
(Mahmudul Islam) ; (Nasim Mahmud Nayan) ; (Ashraful Islam) ; (Sankar Sikder) ; (Masud Rana Rashel) ; (Md Zahangir Alam) |
| DOI |
https://doi.org/10.5573/IEIESPC.2024.13.6.562 |
| Keywords |
Computer vision; Deep learning; Healthcare; Systematic review; Machine learning; State-of-the-art Techniques |
| Abstract |
The advancements in Computer Vision (CV) techniques have demonstrated significant promise in healthcare applications. The adoption of CV within the healthcare sector has drawn considerable attention. The aim of this study is to systematically review and synthesize the recent advancements and applications of CV techniques in various domains of healthcare. 125 papers were selected initially, and after gradual filtering, 20 papers were selected for the final study. In this study, we have identified five medical domains such as disease detection, drug discovery, surgical procedures, human identity decoding, and remote patient monitoring where CV applications are being successfully implemented. Among these domains, the use of CV in surgical assistance is notable. It capitalizes on the precision and efficiency offered by CV. Deep Learning (DL) models show adaptability and accuracy in medical imaging. The combination of computer vision and sensors enhances real-time surgical skills assessment. This study revealed that CV applications can be utilized for predictive analytics and personalized patient treatments. Standardized performance metrics, ethics, and data governance are crucial for responsible computer vision deployment in healthcare. |