Automatic diagnosis of ovarian carcinomas via sparse multiresolution tissue representation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 9349, Issue , 2015, Pages 629-636

  Taieb, Aïcha Ben ^a   Li Chang, Hector ^b   Huntsman, David ^b   Hamarneh, Ghassan ^a  

^a SIMON FRASER UNIVERSITY   (Canada)

^b UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

Histopathology; Machine learning; Ovarian carcinomas

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); GRADING; LEARNING SYSTEMS; TISSUE;

AUTOMATIC DIAGNOSIS; DISCRIMINATIVE FEATURES; HISTOPATHOLOGY; INTEROBSERVER AGREEMENT; LINEAR SUPPORT VECTOR MACHINES; OVARIAN CARCINOMAS; TISSUE REPRESENTATIONS; UNSUPERVISED FEATURE LEARNING;

DIAGNOSIS;

EID: 84947607834     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-24553-9_77     Document Type: Chapter

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