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Proceedings Paper

Curvature-based characterization of shape and internal intensity structure for classification of pulmonary nodules using thin-section CT images
Author(s): Yoshiki Kawata; Noboru Niki; Hironobu Ohmatsu; Masahiko Kusumoto; Ryutaro Kakinuma; Kiyoshi Mori; Hiroyuki Nishiyama; Kenji Eguchi; Masahiro Kaneko; Noriyuki Moriyama
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Paper Abstract

This paper presents a curvature based approach to characterize the internal intensity structure of pulmonary nodules in thin-section CT images. This approach makes use of shape index, curvedness, and CT value to represent locally each voxel in a 3D pulmonary nodule image. From the distribution of shape index, curvedness, and CT value over the 3D pulmonary nodule image a set of 3D moment features, histogram features, and 3D texture features is computed to classify benign and malignant pulmonary nodules. Linear discriminant analysis is used for classification and a receiver operating characteristic (ROC) analysis is used to evaluate the classification accuracy. The potential usefulness of the curvature based features in the computer- aided differential diagnosis is demonstrated by using ROC curves as the performance measure.

Paper Details

Date Published: 21 May 1999
PDF: 12 pages
Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); doi: 10.1117/12.348610
Show Author Affiliations
Yoshiki Kawata, Univ. of Tokushima (Japan)
Noboru Niki, Univ. of Tokushima (Japan)
Hironobu Ohmatsu, National Cancer Ctr. Hospital East (Japan)
Masahiko Kusumoto, National Cancer Ctr. Hospital (Japan)
Ryutaro Kakinuma, National Cancer Ctr. Hospital East (Japan)
Kiyoshi Mori, Tochigi Cancer Ctr. (Japan)
Hiroyuki Nishiyama, The Social Health Insurance Medical Ctr. (Japan)
Kenji Eguchi, National Shikoku Cancer Ctr. Hospital (Japan)
Masahiro Kaneko, National Cancer Ctr. Hospital (Japan)
Noriyuki Moriyama, National Cancer Ctr. Hospital (Japan)


Published in SPIE Proceedings Vol. 3661:
Medical Imaging 1999: Image Processing
Kenneth M. Hanson, Editor(s)

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