Harnessing clinical annotations to improve deep learning performance in prostate segmentation

PURPOSE: Developing large-scale datasets with research-quality annotations is challenging due to the high cost of refining clinically generated markup into high precision annotations. We evaluated the direct use of a large dataset with only clinically generated annotations in development of high-per...

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Detalhes bibliográficos
Publicado no:PLoS One
Main Authors: Sarma, Karthik V., Raman, Alex G., Dhinagar, Nikhil J., Priester, Alan M., Harmon, Stephanie, Sanford, Thomas, Mehralivand, Sherif, Turkbey, Baris, Marks, Leonard S., Raman, Steven S., Speier, William, Arnold, Corey W.
Formato: Artigo
Idioma:Inglês
Publicado em: Public Library of Science 2021
Assuntos:
Research Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC8232529/
https://ncbi.nlm.nih.gov/pubmed/34170972
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0253829
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