An Auto-Contouring Method for Kidney based on SVM. Issue 1 (June 2021)

• Record Type: Journal Article
• Authors: Li, Bo; Xue, Jing; Wang, Ping; Gu, Saikun; Chen, Wei; Qian, Pengjiang; Jiang, Yizhang
• Is Part Of: Journal of physics. Volume 1944:Issue 1(2021)
• Publication Date: 2021-06
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1944/1/012016
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: In adaptive radiotherapy planning, the contour map of the treatment target area is still the most difficult problem. Usually this work is done by a professional radiologist oncologist, which is very time-consuming and labor-intensive. In order to solve this problem, this paper proposes an automatic contour method based on support vector machine. Experiments were conducted on the lower abdomen MR data set of eight patients. In the experiment, the simulated data was only used to train the classifier, and the treatment day images were used to evaluate the performance of the classifier. DSI was used to compare the manual contour and automatic contour of the kidney. The experiment showed that, The automatic contour method based on support vector machine has better classification performance than most classification algorithms. Among the eight sets of results, the DSI value of the six sets of results is 1, and the smallest DSI value is also greater than 9.423.