Art

J-GLOBAL ID：201902286718919233   Reference number：19A0007676

Polyp Classification Using CNN Features from Three Kinds of Endoscope Images

3種類の内視鏡画像からのCNN特徴量を用いたポリープの分類

Author (5)： MURATA MASATAKA (中部大 工) ,  IWAHORI YUJI (中部大 工) ,  USAMI HIROYASU (中部大 工) ,  OGASAWARA NAOTAKA (愛知医大) ,  KASUGAI KUNIO (愛知医大)
Material： 電子情報通信学会技術研究報告  (IEICE Technical Report (Institute of Electronics, Information and Communication Engineers))
Volume： 118  Issue： 150(MI2018 21-31)(Web)  Page： 25-32 (WEB ONLY)  Publication year： Jul. 17, 2018 
JST Material Number： S0532B  ISSN： 0913-5685  Document type： Proceedings
Article type： 原著論文  Country of issue： Japan (JPN)  Language： JAPANESE (JA)

Thesaurus term： medical image ,...
Semi thesaurus term： convolutional neuralnetwork ,...

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JST classification (2)： Diagnosis of tumors(=neoplasms)  (GE03020J) ,  Digestive system diagnosis  (GH02000P)

Reference (11)：

• Y. Mori et al., ′′Novel computer-aided diagnostic system for colorectal lesions by using endocytoscopy (with videos)′′, Gastrointestinal endoscopy, vol.81, no.3, pp.621-629, 2015.
• M. Misawa, et al., ′′Characterization of colorectal lesions using a computer-aided diagnostic system for narrow-band imaging endocytoscopy′′, Gastroenterology, vol.150, no.7, pp.1531-1532, 2016.
• Y. Iwahori, et al., ′′Automatic Polyp Detection from Endoscope Image Using Likelihood Map Based on Edge Information′′, ICPRAM 2017, pp.402-409, 2017.
• Tsubasa Ooto, Hiroyasu Usami, Yuji Iwahori, Aili Wang, Naotaka Ogasawara, Kunio Kasugai, ′′Cost Reduction of Creating Likelihood Map for Automatic Polyp Detection Using Image Pyramid′′, CSII2017, 2017.
• Y. LeCun, et al., ′′Gradient-based learning applied to document recognition′′, Proceedings of the IEEE, vol.86, No.11, pp.2278-2324, 1998.

Terms in the title (5)： 内視鏡画像 ,  CNN ,  特徴量 ,  ポリープ ,  分類