Deep-learning-based automatic segmentation and classification for craniopharyngiomas

Deep-learning-based automatic segmentation and classification for craniopharyngiomas

ObjectiveNeuronavigation 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 remain...

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Bibliographic Details
Main Authors: Xiaorong Yan, Bingquan Lin, Jun Fu, Shuo Li, He Wang, Wenjian Fan, Yanghua Fan, Ming Feng, Renzhi Wang, Jun Fan, Songtao Qi, Changzhen Jiang
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-05-01
Series:Frontiers in Oncology
Subjects:
craniopharyngiomas
QST typing system
deep learning
segmentation
classification
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2023.1048841/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2023.1048841/full

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