Yoshihiro Mitani, Yusuke Fujita, Naofumi Matsunaga, and Yoshihiko Hamamoto
Thin-section computed tomography images, CAD system, Lung opacities classification, Local slice feature vector
A lung opacities classification in thin-section computed tomography(CT) images is expected for designing a computeraided diagnosis(CAD) system. In classifying lung opacities, the effectiveness of slice features has been shown. In this paper, in order further to improve the lung opacities classification performance, we have presented a local slice feature based method.
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