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...

Descripción completa

Detalles Bibliográficos
Autores principales: 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: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8232529/
https://www.ncbi.nlm.nih.gov/pubmed/34170972
http://dx.doi.org/10.1371/journal.pone.0253829

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8232529/
https://www.ncbi.nlm.nih.gov/pubmed/34170972
http://dx.doi.org/10.1371/journal.pone.0253829

Ejemplares similares