RIL-Contour: a Medical Imaging Dataset Annotation Tool for and with Deep Learning

Deep-learning algorithms typically fall within the domain of supervised artificial intelligence and are designed to “learn” from annotated data. Deep-learning models require large, diverse training datasets for optimal model convergence. The effort to curate these datasets is widely regarded as a ba...

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Detalles Bibliográficos
Autores principales: Philbrick, Kenneth A., Weston, Alexander D., Akkus, Zeynettin, Kline, Timothy L., Korfiatis, Panagiotis, Sakinis, Tomas, Kostandy, Petro, Boonrod, Arunnit, Zeinoddini, Atefeh, Takahashi, Naoki, Erickson, Bradley J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6646456/
https://www.ncbi.nlm.nih.gov/pubmed/31089974
http://dx.doi.org/10.1007/s10278-019-00232-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6646456/
https://www.ncbi.nlm.nih.gov/pubmed/31089974
http://dx.doi.org/10.1007/s10278-019-00232-0

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