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Proceedings Paper

Liver cancer detection by using transition features obtained from multi-phase CT images
Author(s): Shigeto Watanabe; Yoshito Mekada; Junichi Hasegawa; Junichiro Toriwaki
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Paper Abstract

This paper presents a method for automated detection of liver cancer regions based on transition of density at each point obtained from multi-phase X-ray CT images. For describing transition of density, two kinds of feature vectors named Density Transition (DT) and Density Change Transition (DCT) are introduced. DCT is used for extraction of cancer candidates and DT is used for suppression of false candidates. In the experiments using 14 real abdominal CT images with cancer, it was shown that the detection rate was 100% and the number of false-positives was 0.71 regions per case.

Paper Details

Date Published: 29 April 2005
PDF: 7 pages
Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); doi: 10.1117/12.595085
Show Author Affiliations
Shigeto Watanabe, Chukyo Univ. (Japan)
Yoshito Mekada, Chukyo Univ. (Japan)
Junichi Hasegawa, Chukyo Univ. (Japan)
Junichiro Toriwaki, Chukyo Univ. (Japan)

Published in SPIE Proceedings Vol. 5747:
Medical Imaging 2005: Image Processing
J. Michael Fitzpatrick; Joseph M. Reinhardt, Editor(s)

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