Deep-learning-based automatic segmentation and classification for craniopharyngiomas

OBJECTIVE: Neuronavigation and classification of craniopharyngiomas can guide surgical approaches and prognostic information. The QST classification has been developed according to the origin of craniopharyngiomas; however, accurate preoperative automatic segmentation and the QST classification rema...

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Detalles Bibliográficos
Autores principales: Yan, Xiaorong, Lin, Bingquan, Fu, Jun, Li, Shuo, Wang, He, Fan, Wenjian, Fan, Yanghua, Feng, Ming, Wang, Renzhi, Fan, Jun, Qi, Songtao, Jiang, Changzhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196103/
https://www.ncbi.nlm.nih.gov/pubmed/37213305
http://dx.doi.org/10.3389/fonc.2023.1048841

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196103/
https://www.ncbi.nlm.nih.gov/pubmed/37213305
http://dx.doi.org/10.3389/fonc.2023.1048841

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