Automated abdominal lymph node segmentation based on RST analysis and SVM

Yukitaka Nimura; Yuichiro Hayashi; Takayuki Kitasaka; Kazuhiro Furukawa; Kazunari Misawa; Kensaku Mori

doi:10.1117/12.2043349

24 March 2014 Automated abdominal lymph node segmentation based on RST analysis and SVM

Yukitaka Nimura, Yuichiro Hayashi, Takayuki Kitasaka, Kazuhiro Furukawa, Kazunari Misawa, Kensaku Mori

Proceedings Volume 9035, Medical Imaging 2014: Computer-Aided Diagnosis; 90352U (2014) https://doi.org/10.1117/12.2043349
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

This paper describes a segmentation method for abdominal lymph node (LN) using radial structure tensor analysis (RST) and support vector machine. LN analysis is one of crucial parts of lymphadenectomy, which is a surgical procedure to remove one or more LNs in order to evaluate them for the presence of cancer. Several works for automated LN detection and segmentation have been proposed. However, there are a lot of false positives (FPs). The proposed method consists of LN candidate segmentation and FP reduction. LN candidates are extracted using RST analysis in each voxel of CT scan. RST analysis can discriminate between difference local intensity structures without influence of surrounding structures. In FP reduction process, we eliminate FPs using support vector machine with shape and intensity information of the LN candidates. The experimental result reveals that the sensitivity of the proposed method was 82.0 % with 21.6 FPs/case.

Citation Download Citation

Yukitaka Nimura, Yuichiro Hayashi, Takayuki Kitasaka, Kazuhiro Furukawa, Kazunari Misawa, and Kensaku Mori "Automated abdominal lymph node segmentation based on RST analysis and SVM", Proc. SPIE 9035, Medical Imaging 2014: Computer-Aided Diagnosis, 90352U (24 March 2014); https://doi.org/10.1117/12.2043349

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available