Discrimination of Lung Sounds using a Statistics of Waveform Intervals

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概要

• 論文の詳細を見る

• In a lung auscultatory sounds diagnosis, the diagnosis result would be affected by the skill of the doctor, that is, the doctor should discriminate a lung sounds by own subjective, since standard diagnosis procedure with objectivity has not been established yet. In many cases of the lung sounds diagnosis, the existence of features, which are called adventitious sounds, are important key. The adventitious sounds is roughly classified into two class; one is called coarse crackles, and the other is called fine crackles. Thus, we construct a computer aided diagnosis (CAD) system for classifying a lung sound into three types, that is, coarse crackle, fine crackle and normal breath sound. We aimed with the waveform time intervals for discrimination. Our CAD system calculates average histograms of intervals for each class, and discriminates a input histogram into these three types by the distance between each average histogram.

• 一般社団法人情報処理学会の論文
• 2006-06-26

著者

• Shoji Kido

  Applied Medical Engineering Sciece Graduate School Of Medicine Yamaguchi University

• Kido Shoji

  Yamaguchi University

• Shouno Hayaru

  Yamaguchi University

• Shouno Hayaru

  Univ. Electro‐communications

• Kido Shoji

  Yamaguchi Univ.

• ORIHASHI Taketoshi

  Yamaguchi University

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• Discrimination of Lung Sounds using a Statistics of Waveform Intervals
• Naive Mean Field Approximation for Sourlas Error Correcting Code(Biocybernetics, Neurocomputing)

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