Medical Imaging and Computer Vision for Artificial Intelligence in Diagnostic Healthcare

Authors

  • Dhananjay A. Kumbhar Department of Electronics and Telecommunication, MIT College of Railway Engineering and Research, Barshi, India.
  • Smita T. Kumbhar Department of Pharmaceutical Chemistry, DSTS Mandal’s College of Pharmacy, Solapur, India.
  • Pushpa D. Jadhav Department of Computer Science and Engineering, Walchand Institute of Technology, Solapur, India.
  • Sushma S. Mule Department of Computer Science and Engineering, MIT College of Railway Engineering and Research, Barshi, India.
  • Amol B. Chounde Department of Electronics and Telecommunication, SVERI's College of Engineering, Pandharpur, India.
  • Mayuri A. Jadhav Department of Electronics and Telecommunication, MIT College of Railway Engineering and Research, Barshi, India.
  • Akshay A. Jadhav Department of Electronics and Telecommunication, MIT College of Railway Engineering and Research, Barshi, India.

Keywords:

Deep learning, Artificial Intelligence, Image processing, Data, Information

Abstract

As AI's unique strategic analytic has increased in accuracy and expanded in applicability, the healthcare industry has become increasingly interested in it. It is proving more and more useful in a number of situations, such as helping to uncover previously unattainable insights into medical decision-making, establishing connections between resources and patients for improved management, and reaping benefits from previously inaccessible data assets. Although hospital imaging data might be difficult to analyze, it is a gold mine of patient information. No matter how talented they are, medical professionals find it extremely difficult to piece together high-resolution images from large data sets of MRI, CAT scans, X-rays, or other testing components. This work shows how a unique AI strategy may be thoroughly investigated across a range of dimensions, leading to exciting new directions for medical imaging research. This examination of the most useful current application demonstrates why it might have therapeutic applications. The potential of artificial intelligence (AI) in the detection of neurological disorders, bone fractures, cancer, and musculoskeletal issues is investigated in this study. The advantages and disadvantages of applying AI to healthcare have also been emphasised. Examining the specifics of AI's function in medical imaging has benefited from qualitative and statistical study of secondary data. Despite assurances to the contrary, a number of researchers have voiced scepticism over the utility of AI in the healthcare industry.

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Published

24.03.2024

How to Cite

A. Kumbhar, D. ., T. Kumbhar, S. ., Jadhav, P. D. ., Mule, S. S. ., Chounde, A. B. ., Jadhav, M. A. ., & Jadhav, A. A. . (2024). Medical Imaging and Computer Vision for Artificial Intelligence in Diagnostic Healthcare. International Journal of Intelligent Systems and Applications in Engineering, 12(3), 376–381. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5261

Issue

Vol. 12 No. 3 (2024)

Section

Research Article

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