An interactive learning framework for scalable classification of pathology images

Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015

Volumn , Issue , 2015, Pages 928-935

  Nalisnik, Michael ^a   Gutman, David A ^a   Kong, Jun ^a   Cooper, Lee A D ^a,b,c  

^a EMORY UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b Emory University   (United States)

^c GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

biomedical image processing; interactive systems; machine learning; pathology

Indexed keywords

ARTIFICIAL INTELLIGENCE; DIAGNOSIS; HISTOLOGY; HOSPITAL DATA PROCESSING; IMAGE PROCESSING; LEARNING SYSTEMS; MEDICAL IMAGE PROCESSING; PATHOLOGY; TISSUE; TUMORS;

ACTIVE-LEARNING PROCESS; COMPUTATIONAL IMAGE ANALYSIS; INTERACTIVE LEARNING; INTERACTIVE SYSTEM; MICROSCOPY IMAGING; PATHOLOGIC DIAGNOSIS; QUANTITATIVE INFORMATION; WHOLE SLIDE IMAGES;

BIG DATA;

EID: 84963740253     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BigData.2015.7363841     Document Type: Conference Paper

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