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The impact of AI applications in prostate segmentation on improving clinical diagnostic and treatment: a review of the literature


Citation

Abdul Rahim, Ezamin and Abduljabbar, H. N. and Mashohor, Syamsiah and Suppiah, Subapriya and Ismael, . (2024) The impact of AI applications in prostate segmentation on improving clinical diagnostic and treatment: a review of the literature. African Journal of Biomedical Research, 27 (3). pp. 715-723. ISSN 1119-5096

Abstract

Prostate cancer is regarded as the second most common cancer in the world. Review of the studies that had been done on this topic for the years 2018-2020by searching in Scopus, ScienceDirect, PubMed, and Google Scholar databases.Keywords used in this searching were medical image processing, prostate ultrasound image segmentation, fuzzy segmentation, CNN segmentation, and deep learning segmentation. The overall obtained articles were 4731, after the limitations of the search strategy, there were only 8articles involved in this study.Findings showed the necessity of prostate segmentation and its role in the diagnosis and treatment improvement; furthermore, there are various approaches to segment prostate gland, but not all of them are suitable to use, due to the accuracy and time limitation.In conclusion, according to the findings of 4articles, which mean50% of the included studies, the results stated that using the CNN algorithm and its different approaches is the highest accuracy methodthat can be used for prostate segmentation.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
Faculty of Medicine and Health Science
Publisher: Ibadan Biomedical Communications Group
Keywords: Medical image processing; Prostate ultrasound image segmentation; Fuzzy segmentation; CNN segmentation; And deep learning segmentation
Depositing User: Ms. Che Wa Zakaria
Date Deposited: 14 May 2025 04:08
Last Modified: 14 May 2025 04:08
URI: http://psasir.upm.edu.my/id/eprint/117319
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