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Proceedings Paper

Investigation of optimal feature value set in false positive reduction process for automated abdominal lymph node detection method
Author(s): Yoshihiko Nakamura; Yukitaka Nimura; Takayuki Kitasaka; Shinji Mizuno; Kazuhiro Furukawa; Hidemi Goto; Michitaka Fujiwara; Kazunari Misawa; Masaaki Ito; Shigeru Nawano; Kensaku Mori
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Paper Abstract

This paper presents an investigation of optimal feature value set in false positive reduction process for the automated method of enlarged abdominal lymph node detection. We have developed the automated abdominal lymph node detection method to aid for surgical planning. Because it is important to understand the location and the structure of an enlarged lymph node in order to make a suitable surgical plan. However, our previous method was not able to obtain the suitable feature value set. This method was able to detect 71.6% of the lymph nodes with 12.5 FPs per case. In this paper, we investigate the optimal feature value set in the false positive reduction process to improve the method for automated abdominal lymph node detection. By applying our improved method by using the optimal feature value set to 28 cases of abdominal 3D CT images, we detected about 74.7% of the abdominal lymph nodes with 11.8 FPs/case.

Paper Details

Date Published: 20 March 2015
PDF: 7 pages
Proc. SPIE 9414, Medical Imaging 2015: Computer-Aided Diagnosis, 94143N (20 March 2015); doi: 10.1117/12.2082500
Show Author Affiliations
Yoshihiko Nakamura, Nagoya Univ. (Japan)
Yukitaka Nimura, Nagoya Univ. (Japan)
Takayuki Kitasaka, Aichi Institute of Technology (Japan)
Shinji Mizuno, Aichi Institute of Technology (Japan)
Kazuhiro Furukawa, Nagoya Univ. (Japan)
Hidemi Goto, Nagoya Univ. (Japan)
Michitaka Fujiwara, Nagoya Univ. (Japan)
Kazunari Misawa, Aichi Cancer Ctr. Hospital (Japan)
Masaaki Ito, National Cancer Ctr. Hospital East (Japan)
Shigeru Nawano, International Univ. of Health and Welfare (Japan)
Kensaku Mori, Nagoya Univ. (Japan)


Published in SPIE Proceedings Vol. 9414:
Medical Imaging 2015: Computer-Aided Diagnosis
Lubomir M. Hadjiiski; Georgia D. Tourassi, Editor(s)

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