Art
J-GLOBAL ID：201802216443310335
Reference number：18A0770751
Deep learning with convolutional neural network in radiology
放射線学での畳込みニューラルネットワークを用いた深層学習
Author (5)：
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Material：
Volume：
36
Issue：
4
Page：
257-272
Publication year：
Apr. 25, 2018
JST Material Number：
L3853A
ISSN：
1867-1071
Document type：
Article
Article type：
文献レビュー
Country of issue：
Germany, Federal Republic of (DEU)
Language：
ENGLISH (EN)
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Semi thesaurus term：
Thesaurus term/Semi thesaurus term
Keywords indexed to the article.
All keywords is available on JDreamIII(charged).
On J-GLOBAL, this item will be available after more than half a year after the record posted. In addtion, medical articles require to login to MyJ-GLOBAL.
,...
JST classification (1)：
JST classification
Category name(code) classified by JST.
Clinical radiology in general
Reference (74)：
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LeCun Y, Bengio Y, Hinton G. Deep learning. Nature. 2015;521:436-44.
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Fukushima K, Miyake S. Neocognitron: a new algorithm for pattern recognition tolerant of deformations and shifts in position. Pattern Recognit. 1982;15:455-69.
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Hubel DH, Wiesel TN. Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. J Physiol. 1962;160:106-54.
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Krizhevsky A, Sutskever I, Hinton G. ImageNet classification with deep convolutional neural networks. Advances in Neural Information Processing System 25 (NIPS 2012). 2012. https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks:Published. Accessed 14 Dec 2017.
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Kahn CE Jr. From images to actions: opportunities for artificial intelligence in radiology. Radiology. 2017;285:719-20.
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Terms in the title
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