A Survey of Soft Computing Approaches in Biomedical Imaging. (3rd August 2021)

• Record Type: Journal Article
• Authors: Devi, Manju; Singh, Sukhdip; Tiwari, Shailendra; Chandra Patel, Subhash; Ayana, Melkamu Teshome
• Other Names: Kang Jiawen Academic Editor.
• Is Part Of: Journal of healthcare engineering. Volume 2021(2021)
• Publication Date: 2021-08-03
• Subjects: Hospital buildings -- Environmental engineering -- Periodicals; Medical technology -- Periodicals; Medical informatics -- Periodicals; 610.28
• DOI: 10.1155/2021/1563844
• Languages: English
• ISSNs: 2040-2295

Abstract

Abstract : Medical imaging is an essential technique for the diagnosis and treatment of diseases in modern clinics. Soft computing plays a major role in the recent advances in medical imaging. It handles uncertainties and improves the qualities of an image. Until now, various soft computing approaches have been proposed for medical applications. This paper discusses various medical imaging modalities and presents a short review of soft computing approaches such as fuzzy logic, artificial neural network, genetic algorithm, machine learning, and deep learning. We also studied and compared each approach used for other imaging modalities based on the certain parameter used for the system evaluation. Finally, based on comparative analysis, the possible research strategies for further development are proposed. As far as we know, no previous work examined this issue.