A Review of Semantic Medical Image Segmentation Based on Different Paradigms

Jianquan Tan, Wenrui Zhou, Ling Lin and Huxidan Jumahong
Additional contact information
Jianquan Tan: Key Laboratory of Intelligent Computing Research and Application, Yili Normal University, Yining, China & School of Network Security and Information Technology, Yili Normal University, Yining, China
Wenrui Zhou: Key Laboratory of Intelligent Computing Research and Application, Yili Normal University, Yining, China & School of Network Security and Information Technology, Yili Normal University, Yining, China
Ling Lin: Key Laboratory of Intelligent Computing Research and Application, Yili Normal University, Yining, China & School of Network Security and Information Technology, Yili Normal University, Yining, China
Huxidan Jumahong: Key Laboratory of Intelligent Computing Research and Application, Yili Normal University, Yining, China & School of Network Security and Information Technology, Yili Normal University, Yining, China

International Journal on Semantic Web and Information Systems (IJSWIS), 2024, vol. 20, issue 1, 1-25

Abstract: In recent years, with the widespread application of medical images, the rapid and accurate identification of these regions of interest in a large number of medical images has received widespread attention. This article provides a review of medical image segmentation methods based on deep learning. Firstly, an overview of medical image segmentation methods was provided in the relevant knowledge, segmentation types, segmentation processes, and image processing applications. Secondly, the applications of supervised, semi supervised, and unsupervised methods in medical image segmentation were discussed, and their advantages, disadvantages, and applicable scenarios were revealed through the application of a large number of specific segmentation examples in practical scenarios. Finally, the commonly used medical image segmentation datasets and evaluation indicators were introduced, and the current medical image segmentation methods were summarized and prospected. This review provides a comprehensive and in-depth understanding for researchers in the field of medical image segmentation, and provides valuable references for the design and implementation of future related work.

Date: 2024
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJSWIS.345246 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jswis0:v:20:y:2024:i:1:p:1-25

Access Statistics for this article

International Journal on Semantic Web and Information Systems (IJSWIS) is currently edited by Brij Gupta

More articles in International Journal on Semantic Web and Information Systems (IJSWIS) from IGI Global
Bibliographic data for series maintained by Journal Editor ().