Triaging diagnostically relevant regions from pathology whole slides of breast cancer: A texture based approach

IEEE Transactions on Medical Imaging

Volumn 35, Issue 1, 2016, Pages 307-315

  Peikari, Mohammad ^a   Gangeh, Mehrdad J ^a   Zubovits, Judit ^a   Clarke, Gina ^b   Martel, Anne L ^a,b  

^a UNIVERSITY OF TORONTO   (Canada)

^b Canada   (Canada)

Author keywords

Bag of visual words; Breast cancer; Fast means; Image analysis; Machine learning; Pathology; Texture

Indexed keywords

ARTIFICIAL INTELLIGENCE; DISEASES; GRAPHIC METHODS; IMAGE ANALYSIS; LEARNING SYSTEMS; MEDICAL IMAGING; PATHOLOGY; TEXTURES; TISSUE;

AREA UNDER THE ROC CURVE; BAG-OF-VISUAL-WORDS; BREAST CANCER; EXPERIMENTAL ANALYSIS; FAST-MEANS; INTENSITY-BASED METHODS; SUPPORT VECTOR MACHINE CLASSIFIERS; TEXTURE BASED APPROACHES;

IMAGE TEXTURE;

EOSIN; HEMATOXYLIN;

ARTICLE; BREAST CANCER; CLINICAL ARTICLE; COLOR; HISTOGRAM; HUMAN; HUMAN TISSUE; IMAGE ANALYSIS; PATHOLOGY; RECEIVER OPERATING CHARACTERISTIC; SUPPORT VECTOR MACHINE; TISSUE STRUCTURE; WHOLE SLIDE IMAGE; BREAST NEOPLASMS; COMPUTER ASSISTED DIAGNOSIS; FEMALE; MACHINE LEARNING; PROCEDURES;

BREAST NEOPLASMS; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MACHINE LEARNING; ROC CURVE;

EID: 84959351687     PISSN: 02780062     EISSN: 1558254X     Source Type: Journal    
DOI: 10.1109/TMI.2015.2470529     Document Type: Article

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