A comparison study of feature selection algorithms for automatic differentiation of obstructive lung diseases
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概要
- 論文の詳細を見る
The study was conducted to test and compare the performance of several feature selection methods for the differentiation among obstructive lung diseases based on the features from texture and shape analysis using HRCT (High Resolution Computerized Tomography) images. Five different types of feature selection methods were tested and compared based on the classification performance and clinical applicability. Based on the experimental results, we investigate characteristics of those feature selection methods and evaluate in terms of classification accuracy, robustness, number of iteration and computation time. Especially, SFFS give users good advantage that can terminate the algorithm earlier without accuracy lost.
- 社団法人電子情報通信学会の論文
- 2007-01-19
著者
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Kang Suk
Department of Materials Science and Engineering, Seoul National University
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Lee Youngjoo
Department Of Industrial Engineering Seoul National University College Of Engineering
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Kang Suk
Department Of Industrial Engineering Seoul National University College Of Engineering
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Kang Suk
Department Of Applied Physics Faculty Of Engineering Osaka University
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Lee June
Seoul National Univ. Seoul Kor
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Kim Namkug
Department of Radiology, Asan Medical Center
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Seo Joon
Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine
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Kim Song
Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine
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Sung Yu-Sub
Department of Industrial Engineering, Seoul National University College of Engineering
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Park Bumwo
Department of Industrial Engineering, Seoul National University College of Engineering
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Lee JuneGoo
Department of Radiology, Seoul National University College of Medicine
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Kim Namkug
Department Of Radiology Asan Medical Center
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Kim Namkug
Department Of Industrial Engineering Seoul National University
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Park Bumwo
Department Of Industrial Engineering Seoul National University College Of Engineering
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Sung Yu-sub
Department Of Industrial Engineering Seoul National University College Of Engineering
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Seo Joon
Department Of Radiology And Research Institute Of Radiology University Of Ulsan College Of Medicine
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Kim Song
Department Of Radiology And Research Institute Of Radiology University Of Ulsan College Of Medicine
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Kim Song
Department Of Geography Kyung Hee University
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Kim Song
Department Of Dermatology Samsung Medical Center Sungkyunkwan University School Of Medicine
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Kim Song
Department Of Biological Science Kongju National University
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