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10th International Conference on Image Analysis and Processing (ICIAP'99)
Computer Aided Differential Diagnosis of Pulmonary Nodules Using Curvature Based Analysis
Venice, Italy
September 27-September 29
ISBN: 0-7695-0040-4
Y. Kawata, University of Tokushima
N. Niki, University of Tokushima
H. Ohmatsu, National Cancer Center East
R. Kakinuma, National Cancer Center East
K. Mori, Tochigi Cancer Center
K. Eguchi, National Shikoku Cancer Center
M. Kaneko, National Cancer Center
N. Moriyama, National Cancer Center
M. Kusumoto, National Cancer Center
H. Nishiyama, The Social Health Insurance Medical Center
This paper focuses on characterizing the internal intensity structure of pulmonary nodules in thin-section CT images for classification between benign and malignant nodules. This approach makes use of shape index, curvedness, and CT density to represent locally each voxel constructing the three-dimensional (3D) pulmonary nodule image. From the distribution of shape index, curvedness, and CT density over the 3D pulmonary nodule image a set of histogram features, and 3D texture features is computed to classify benign and malignant 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.
Citation:
Y. Kawata, N. Niki, H. Ohmatsu, R. Kakinuma, K. Mori, K. Eguchi, M. Kaneko, N. Moriyama, M. Kusumoto, H. Nishiyama, "Computer Aided Differential Diagnosis of Pulmonary Nodules Using Curvature Based Analysis," iciap, pp.470, 10th International Conference on Image Analysis and Processing (ICIAP'99), 1999
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