Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology Images

IEEE Transactions on Medical Imaging

Volumn 35, Issue 9, 2016, Pages 2141-2150

  Ehteshami Bejnordi, Babak ^a   Balkenhol, Maschenka ^a   Litjens, Geert ^b   Holland, Roland ^a   Bult, Peter ^a   Karssemeijer, Nico ^a   Van Der Laak, Jeroen A W M ^a  

^a RADBOUD UNIVERSITY MEDICAL CENTER   (Netherlands)

^b UNIVERSITY OF HEIDELBERG   (Germany)

Author keywords

Computer aided diagnosis; DCIS Detection; H E staining; Whole Slide imaging

Indexed keywords

COMPUTER AIDED DIAGNOSIS; TISSUE; TISSUE ENGINEERING;

ARCHITECTURAL FEATURES; AUTOMATED DETECTION; DETECTION ALGORITHM; DUCTAL CARCINOMA IN SITU; SPATIAL CLUSTERING; STRUCTURAL TEXTURES; WHOLE SLIDE IMAGES; WHOLE SLIDE IMAGING (WSI);

MEDICAL IMAGING;

EOSIN; HEMATOXYLIN;

ARTICLE; CANCER DIAGNOSIS; CLASSIFICATION ALGORITHM; CLINICAL EFFECTIVENESS; COMPUTER ASSISTED DIAGNOSIS; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; FALSE POSITIVE RESULT; HISTOPATHOLOGY; HUMAN; HUMAN TISSUE; IMMUNOHISTOCHEMISTRY; INTRADUCTAL CARCINOMA; RANDOM FOREST; RECEIVER OPERATING CHARACTERISTIC; ALGORITHM; BREAST; BREAST TUMOR; PAGET NIPPLE DISEASE;

ALGORITHMS; BREAST; BREAST NEOPLASMS; CARCINOMA, DUCTAL, BREAST; CARCINOMA, INTRADUCTAL, NONINFILTRATING; HUMANS;

EID: 84985995876     PISSN: 02780062     EISSN: 1558254X     Source Type: Journal    
DOI: 10.1109/TMI.2016.2550620     Document Type: Article

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