Share Email Print

Proceedings Paper

Ensemble lymph node detection from CT volumes combining local intensity structure analysis approach and appearance learning approach
Author(s): Yoshihiko Nakamura; Yukitaka Nimura; Masahiro Oda; Takayuki Kitasaka; Kazuhiro Furukawa; Hidemi Goto; Michitaka Fujiwara; Kazunari Misawa; Kensaku Mori
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

This paper presents an ensemble lymph node detection method combining two automated lymph node detection methods from CT volumes. Detecting enlarged abdominal lymph nodes from CT volumes is an important task for the pre-operative diagnosis and planning done for cancer surgery. Although several research works have been conducted toward achieving automated abdominal lymph node detection methods, such methods still do not have enough accuracy for detecting lymph nodes of 5 mm or larger. This paper proposes an ensemble lymph node detection method that integrates two different lymph node detection schemes: (1) the local intensity structure analysis approach and (2) the appearance learning approach. This ensemble approach is introduced with the aim of achieving high sensitivity and specificity. Each component detection method is independently designed to detect candidate regions of enlarged abdominal lymph nodes whose diameters are over 5 mm. We applied the proposed ensemble method to 22 cases using abdominal CT volumes. Experimental results showed that we can detect about 90.4% (47/52) of the abdominal lymph nodes with about 15.2 false-positives/case for lymph nodes of 5mm or more in diameter.

Paper Details

Date Published: 24 March 2016
PDF: 7 pages
Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 97852X (24 March 2016); doi: 10.1117/12.2214925
Show Author Affiliations
Yoshihiko Nakamura, Tomakomai National College of Technology (Japan)
Yukitaka Nimura, Nagoya Univ. (Japan)
Masahiro Oda, Nagoya Univ. (Japan)
Takayuki Kitasaka, 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)
Kensaku Mori, Nagoya Univ. (Japan)

Published in SPIE Proceedings Vol. 9785:
Medical Imaging 2016: Computer-Aided Diagnosis
Georgia D. Tourassi; Samuel G. Armato III, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?