Volume 35, Issue 5 · TMI Watch

May 2016 · Volume 35, Issue 5 · Vol. 35 · Issue 5 · DOI 10.1109/TMI.2016.2528162

Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning

中文标题翻译待生成

Hoo-Chang Shin, Holger R. Roth, Mingchen Gao, Le Lu, Ziyue Xu, Isabella Nogues, Jianhua Yao, Daniel Mollura

Body Part 身体部位

Modality 模态

Abstract / 摘要

English

Remarkable progress has been made in image recognition, primarily due to the availability of large-scale annotated datasets and deep convolutional neural networks (CNNs). CNNs enable learning data-driven, highly representative, hierarchical image features from sufficient training data. However, obtaining datasets as comprehensively annotated as ImageNet in the medical imaging domain remains a chal...

中文

中文摘要翻译待生成

Author Info / 作者信息

Hoo-Chang Shin Affiliation not provided by IEEE Xplore 机构中文翻译待生成或 IEEE 未提供机构

Holger R. Roth Affiliation not provided by IEEE Xplore 机构中文翻译待生成或 IEEE 未提供机构

Mingchen Gao Affiliation not provided by IEEE Xplore 机构中文翻译待生成或 IEEE 未提供机构

Le Lu Affiliation not provided by IEEE Xplore 机构中文翻译待生成或 IEEE 未提供机构

Ziyue Xu Affiliation not provided by IEEE Xplore 机构中文翻译待生成或 IEEE 未提供机构

Isabella Nogues Affiliation not provided by IEEE Xplore 机构中文翻译待生成或 IEEE 未提供机构

Jianhua Yao Affiliation not provided by IEEE Xplore 机构中文翻译待生成或 IEEE 未提供机构

Daniel Mollura Affiliation not provided by IEEE Xplore 机构中文翻译待生成或 IEEE 未提供机构

Translation pending Article 7404017