Development of in-house fully residual deep convolutional neural network-based segmentation software for the male pelvic CT

BACKGROUND: This study aimed to (1) develop a fully residual deep convolutional neural network (CNN)-based segmentation software for computed tomography image segmentation of the male pelvic region and (2) demonstrate its efficiency in the male pelvic region. METHODS: A total of 470 prostate cancer...

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Detalles Bibliográficos
Autores principales: Hirashima, Hideaki, Nakamura, Mitsuhiro, Baillehache, Pascal, Fujimoto, Yusuke, Nakagawa, Shota, Saruya, Yusuke, Kabasawa, Tatsumasa, Mizowaki, Takashi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8299691/
https://www.ncbi.nlm.nih.gov/pubmed/34294090
http://dx.doi.org/10.1186/s13014-021-01867-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8299691/
https://www.ncbi.nlm.nih.gov/pubmed/34294090
http://dx.doi.org/10.1186/s13014-021-01867-6

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