The use of a local histogram feature vector of classifying diffuse lung opacities in high-resolution computed tomography

Authors:
Yoshihiro Mitani;Yusuke Fujita;Naofumi Matsunaga;Yoshihiko Hamamoto
Affiliations:
Department of Intelligent System Engineering, Ube National College of Technology, Ube, Yamaguchi, Japan;Graduate School of Medicine, Yamaguchi University, Ube, Yamaguchi, Japan;Graduate School of Medicine, Yamaguchi University, Ube, Yamaguchi, Japan;Department of Intelligent System Engineering, Ube National College of Technology, Ube, Yamaguchi, Japan
Venue:
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
Year:
2012

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Abstract

The classification of diffuse lung opacities in high-resolution computed tomography(HRCT) images is an important step for developing a computer-aided diagnosis(CAD) system. In designing the CAD system for classifying diffuse lung opacities in HRCT images, a histogram feature has been shown to be effective. In order to improve further the classification performance of the CAD system, we have proposed the use of a local histogram feature vector. The experimental results show that the proposed method leads to clear improvement of the classification performance.