Share Email Print

Proceedings Paper

Automatic mediastinal lymph node detection in chest CT
Author(s): Marco Feuerstein; Daisuke Deguchi; Takayuki Kitasaka; Shingo Iwano; Kazuyoshi Imaizumi; Yoshinori Hasegawa; Yasuhito Suenaga; Kensaku Mori
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Computed tomography (CT) of the chest is a very common staging investigation for the assessment of mediastinal, hilar, and intrapulmonary lymph nodes in the context of lung cancer. In the current clinical workflow, the detection and assessment of lymph nodes is usually performed manually, which can be error-prone and timeconsuming. We therefore propose a method for the automatic detection of mediastinal, hilar, and intrapulmonary lymph node candidates in contrast-enhanced chest CT. Based on the segmentation of important mediastinal anatomy (bronchial tree, aortic arch) and making use of anatomical knowledge, we utilize Hessian eigenvalues to detect lymph node candidates. As lymph nodes can be characterized as blob-like structures of varying size and shape within a specific intensity interval, we can utilize these characteristics to reduce the number of false positive candidates significantly. We applied our method to 5 cases suspected to have lung cancer. The processing time of our algorithm did not exceed 6 minutes, and we achieved an average sensitivity of 82.1% and an average precision of 13.3%.

Paper Details

Date Published: 4 March 2009
PDF: 11 pages
Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 72600V (4 March 2009); doi: 10.1117/12.811101
Show Author Affiliations
Marco Feuerstein, Nagoya Univ. (Japan)
Daisuke Deguchi, Nagoya Univ. (Japan)
Takayuki Kitasaka, Nagoya Univ. (Japan)
Aichi Institute of Technology (Japan)
Shingo Iwano, Nagoya Univ. (Japan)
Kazuyoshi Imaizumi, Nagoya Univ. (Japan)
Yoshinori Hasegawa, Nagoya Univ. (Japan)
Yasuhito Suenaga, Nagoya Univ. (Japan)
Kensaku Mori, Nagoya Univ. (Japan)

Published in SPIE Proceedings Vol. 7260:
Medical Imaging 2009: Computer-Aided Diagnosis
Nico Karssemeijer; Maryellen L. Giger, 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?