Deep learning-based assessment of tumor-associated stroma for diagnosing breast cancer in histopathology images

Proceedings - International Symposium on Biomedical Imaging

Volumn , Issue , 2017, Pages 929-932

  Ehteshami Bejnordi, Babak ^a,b   Lin, Jimmy ^d   Glass, Ben ^b   Mullooly, Maeve ^c   Gierach, Gretchen L ^a   Sherman, Mark E ^e   Karssemeijer, Nico ^a   Van Der Laak, Jeroen ^a   Beck, Andrew H ^b  

^a RADBOUD UNIVERSITY MEDICAL CENTER   (Netherlands)

^b HARVARD MEDICAL SCHOOL   (United States)

^c NATIONAL CANCER INSTITUTE   (United States)

^d The Harker School   (United States)

^e MAYO CLINIC   (United States)

Author keywords

Breast Cancer; Convolutional Neural Networks; Digital pathology; Tumor Associated Stroma

Indexed keywords

AUTOMATION; CONVOLUTION; DEEP LEARNING; DIAGNOSIS; DISEASES; NEURAL NETWORKS; TISSUE; TUMORS;

AUTOMATED SYSTEMS; BREAST CANCER; BREAST CARCINOMAS; CONVOLUTIONAL NEURAL NETWORK; DIAGNOSTIC BIOMARKERS; DIGITAL PATHOLOGIES; DISCRIMINATIVE POWER; EPITHELIAL TISSUE;

MEDICAL IMAGING;

EID: 85023173631     PISSN: 19457928     EISSN: 19458452     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2017.7950668     Document Type: Conference Paper

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