Dose-Distribution-Driven PET Image-Based Outcome Prediction (DDD-PIOP): A Deep Learning Study for Oropharyngeal Cancer IMRT Application

PURPOSE: To develop a deep learning-based AI agent, DDD-PIOP (Dose-Distribution-Driven PET Image Outcome Prediction), for predicting (18)FDG-PET image outcomes of oropharyngeal cancer (OPC) in response to intensity-modulated radiation therapy (IMRT). METHODS: DDD-PIOP uses pre-radiotherapy (18)FDG-P...

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Detalles Bibliográficos
Autores principales: Wang, Chunhao, Liu, Chenyang, Chang, Yushi, Lafata, Kyle, Cui, Yunfeng, Zhang, Jiahan, Sheng, Yang, Mowery, Yvonne, Brizel, David, Yin, Fang-Fang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7461989/
https://www.ncbi.nlm.nih.gov/pubmed/33014811
http://dx.doi.org/10.3389/fonc.2020.01592

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7461989/
https://www.ncbi.nlm.nih.gov/pubmed/33014811
http://dx.doi.org/10.3389/fonc.2020.01592

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