Deep Interactive Learning-based ovarian cancer segmentation of H&E-stained whole slide images to study morphological patterns of BRCA mutation

• Egile Nagusiak: David Joon Ho (Egilea), M. Herman Chui (Egilea), Chad M. Vanderbilt (Egilea), Jiwon Jung (Egilea), Mark E. Robson (Egilea), Chan-Sik Park (Egilea), Jin Roh (Egilea), Thomas J. Fuchs (Egilea)
• Formatua: Liburua
• Argitaratua: Elsevier, 2023-01-01T00:00:00Z.
• Gaiak: article
• Sarrera elektronikoa: Connect to this object online.

Deep learning has been widely used to analyze digitized hematoxylin and eosin (H&E)-stained histopathology whole slide images. Automated cancer segmentation using deep learning can be used to diagnose malignancy and to find novel morphological patterns to predict molecular subtypes. To train pix...