Application of the Sugeno Integral with λ-Fuzzy Measures to Endoscopic Diagnosis
スポンサーリンク
概要
- 論文の詳細を見る
This paper presents an application of a fuzzy integral model to an endoscopic image diagnosis and an examination of the model structure. Measures derived from human subjectivity do not usually possess additivity; thus, fuzzy measures requiring monotonicity rather than additivity can be treated as subjective measures of the person evaluating an object. In medical diagnostic imaging, even though images have no ambiguity and their items are strictly quantified, these values are more or less subjective. In the present study, the Sugeno integral model with λ-fuzzy measures for distinguishing a gastric ulcer from a gastric carcinoma was constructed using input-output data obtained from a physician. The model parameters were optimized using a method involving a genetic algorithm. As a result, the items having a high importance degree in the model corresponded with the items estimated by the physician to have a high importance degree.
- バイオメディカル・ファジィ・システム学会の論文
著者
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Saito Masao
Research Center For Advanced Technologies Tokyo Denki University
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NOTOMI Kazuhiro
Department of Information and Computer Sciences, Kanagawa Institute of Technology
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Saito Keiichi
Research Center For Advanced Technologies Tokyo Denki University
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Notomi Kazuhiro
Department Of Information And Computer Sciences Kanagawa Institute Of Technology
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Hashimoto Hiroshi
Department Of Adult Disease Jr Tokyo General Hospital
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Hashimoto H
Division Of Quality Control Research Center For Biologicals The Kitasato Institute
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SAITO Keiichi
Superconductivity Research Laboratory, Tokyo Denki University
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HASHIMOTO Hiroshi
Institute of Geriatrics, Tokyo Women's Medical University
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SAITO Masao
Superconductivity Research Laboratory, Tokyo Denki University
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HASHIMOTO HIROSHI
Institute of Geriatrics, Tokyo Women's Medical University
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