Clinical Enhancement in AI-Based Post-processed Fast-Scan Low-Dose CBCT for Head and Neck Adaptive Radiotherapy

Purpose: To assess image quality and uncertainty in organ-at-risk segmentation on cone beam computed tomography (CBCT) enhanced by deep-learning convolutional neural network (DCNN) for head and neck cancer. Methods: An in-house DCNN was trained using forty post-operative head and neck cancer patient...

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Detalles Bibliográficos
Autores principales: Chen, Wen, Li, Yimin, Yuan, Nimu, Qi, Jinyi, Dyer, Brandon A., Sensoy, Levent, Benedict, Stanley H., Shang, Lu, Rao, Shyam, Rong, Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7904899/
https://www.ncbi.nlm.nih.gov/pubmed/33733226
http://dx.doi.org/10.3389/frai.2020.614384

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7904899/
https://www.ncbi.nlm.nih.gov/pubmed/33733226
http://dx.doi.org/10.3389/frai.2020.614384

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