A Computer-aided Diagnosis Method for Classification of Pneumoconiosis Patterns on HRCT Images

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概要

• 論文の詳細を見る

• This paper describes a computer-aided diagnosis method to classify pneumoconiosis on HRCT images. In Japan, the pneumoconiosis is divided into: Type 1(no nodules), Type 2(few small nodules), Type 3-a(numerous small nodules) and Type 3-b(numerous small nodules and presence of large nodules). The classification is performed as follows. Firstly extracting large-sized nodules and recognizing the type 3-b cases. Secondly, employing Hessian-based filters to detect small-sized nodules on the rest cases. Finally, adopting a bag-of-features-based method to classify the other three kinds of cases. The proposed method achieved the classification accuracy of 90.6%, which would be helpful to classify pneumoconiosis on HRCT.

• 2012-10-22

著者

• KIDO SHOJI

  Applied Medical Engineering Science, Graduate School of Medicine, Yamaguchi University

• Kido Shoji

  Applied Medical Engineering Science Graduate School Of Medicine Yamaguchi University

• Xu Rui

  Applied Computational Intelligence Laboratory Department Of Electrical And Computer Engineering Univ

• Hirano Yasushi

  Applied Medical Engineering Science Graduate School Of Medicine Yamaguchi University

• Suganuma Narufumi

  Department Of Environmental Medicine Kochi Medical School

• ZHAO Wei

  Applied Medical Engineering Science, Graduate School of Medicine, Yamaguchi University

• SUGANUMA Narufumi

  Department of Environmental Medicine Kochi Medical School, Kochi University

• TACHIBANA Rie

  Information Science and Technology Dept., Oshima National College of Maritime Technology

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