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Quantitative analysis and development of a computer-aided system for identification of regular pit patterns of colorectal lesions

https://hiroshima.repo.nii.ac.jp/records/2006916
https://hiroshima.repo.nii.ac.jp/records/2006916
58a93c06-fbbd-41e4-9edf-4876dc11f7b7
名前 / ファイル ライセンス アクション
GastrointestEndosc_72_1047.pdf GastrointestEndosc_72_1047.pdf (739.0 KB)
Item type デフォルトアイテムタイプ_(フル)(1)
公開日 2023-03-18
タイトル
タイトル Quantitative analysis and development of a computer-aided system for identification of regular pit patterns of colorectal lesions
言語 en
作成者 Takemura, Yoshito

× Takemura, Yoshito

en Takemura, Yoshito

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Yoshida, Shigeto

× Yoshida, Shigeto

en Yoshida, Shigeto

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Tanaka, Shinji

× Tanaka, Shinji

en Tanaka, Shinji

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Onji, Keiichi

× Onji, Keiichi

en Onji, Keiichi

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Oka, Shiro

× Oka, Shiro

en Oka, Shiro

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Tamaki, Toru

× Tamaki, Toru

en Tamaki, Toru

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Kaneda, Kazufumi

× Kaneda, Kazufumi

en Kaneda, Kazufumi

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Yoshihara, Masaharu

× Yoshihara, Masaharu

en Yoshihara, Masaharu

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Chayama, Kazuaki

× Chayama, Kazuaki

en Chayama, Kazuaki

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アクセス権
アクセス権 open access
アクセス権URI http://purl.org/coar/access_right/c_abf2
権利情報
権利情報 Copyright (c) 2010 American Society for Gastrointestinal Endoscopy Published by Mosby, Inc.
主題
主題Scheme NDC
主題 490
内容記述
内容記述 Background: Because pit pattern classification of colorectal lesions is clinically useful in determining treatment options for colorectal tumors but requires extensive training, we developed a computerized system to automatically quantify and thus classify pit patterns depicted on magnifying endoscopy images. Objective: To evaluate the utility and limitations of our automated pit pattern classification system. Design: Retrospective study. Setting: Department of endoscopy at a university hospital. Main Outcome Measurements: Performance of our automated computer-based system for classification of pit patterns on magnifying endoscopic images in comparison to classification by diagnosis of the 134 regular pit pattern images by an endoscopist. Results: For type I and II pit patterns, the results of discriminant analysis were in complete agreement with the endoscopic diagnoses. Type IIIL was diagnosed in 29 of 30 cases (96.7%) and type IV was diagnosed in 1 case. Twenty-nine of 30 cases (96.7%) were diagnosed as type IV pit pattern. The overall accuracy of our computerized recognition system was 132 of 134 (98.5%). Conclusions: Our system is best characterized as semiautomated but is a step toward the development of a fully automated system to assist in the diagnosis of colorectal lesions based on classification of pit patterns.
言語 en
出版者
出版者 Mosby Elsevier
言語
言語 eng
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_6501
資源タイプ journal article
出版タイプ
出版タイプ AO
出版タイプResource http://purl.org/coar/version/c_b1a7d7d4d402bcce
関連情報
識別子タイプ DOI
関連識別子 10.1016/j.gie.2010.07.037
関連情報
識別子タイプ DOI
関連識別子 http://dx.doi.org/10.1016/j.gie.2010.07.037
収録物識別子
収録物識別子タイプ ISSN
収録物識別子 0016-5107
収録物識別子
収録物識別子タイプ NCID
収録物識別子 AA00653961
開始ページ
開始ページ 1047
書誌情報 Gastrointestinal Endoscopy
Gastrointestinal Endoscopy

巻 72, 号 5, p. 1047-1051, 発行日 2010-11
旧ID 30870
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