Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features

BMC Bioinformatics

Volumn 18, Issue 1, 2017, Pages

  Xu, Yan ^a,b   Jia, Zhipeng ^b,c   Wang, Liang Bo ^b,d   Ai, Yuqing ^b,c   Zhang, Fang ^b,c   Lai, Maode ^e   Chang, Eric I Chao ^b  

^a BEIHANG UNIVERSITY   (China)

^b MICROSOFT RESEARCH   (United States)

^c TSINGHUA UNIVERSITY   (China)

^d NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^e ZHEJIANG UNIVERSITY SCHOOL OF MEDICINE   (China)

Author keywords

Classification; Deep convolution activation feature; Deep learning; Feature learning; Segmentation

Indexed keywords

BRAIN; CHEMICAL ACTIVATION; CLASSIFICATION (OF INFORMATION); CONVOLUTION; DEEP LEARNING; DEEP NEURAL NETWORKS; DIAGNOSIS; DISEASES; IMAGE ANALYSIS; IMAGE CLASSIFICATION; NEURAL NETWORKS; TISSUE; TUMORS; VISUALIZATION;

AUTOMATIC ANALYSIS; BIOLOGICAL INSIGHT; CONVOLUTIONAL NEURAL NETWORK; DEEP CONVOLUTION ACTIVATION FEATURE; DIGITAL PATHOLOGIES; FEATURE LEARNING; NATURAL IMAGE DATABASE; STATE-OF-THE-ART PERFORMANCE;

IMAGE SEGMENTATION;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; BRAIN NEOPLASMS; CARCINOMA; COLONIC NEOPLASMS; HUMAN; IMAGE PROCESSING; PATHOLOGY; PROCEDURES; SUPPORT VECTOR MACHINE;

ALGORITHMS; BRAIN NEOPLASMS; CARCINOMA; COLONIC NEOPLASMS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; NEURAL NETWORKS (COMPUTER); SUPPORT VECTOR MACHINE;

EID: 85019707351     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/s12859-017-1685-x     Document Type: Article

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