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

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...

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Detalles Bibliográficos
Autores principales: Ho, David Joon, Chui, M. Herman, Vanderbilt, Chad M., Jung, Jiwon, Robson, Mark E., Park, Chan-Sik, Roh, Jin, Fuchs, Thomas J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Original Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758515/
https://www.ncbi.nlm.nih.gov/pubmed/36536772
http://dx.doi.org/10.1016/j.jpi.2022.100160

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758515/
https://www.ncbi.nlm.nih.gov/pubmed/36536772
http://dx.doi.org/10.1016/j.jpi.2022.100160

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