An Automatic Deep Learning–Based Workflow for Glioblastoma Survival Prediction Using Preoperative Multimodal MR Images: A Feasibility Study

PURPOSE: Most radiomic studies use the features extracted from the manually drawn tumor contours for classification or survival prediction. However, large interobserver segmentation variations lead to inconsistent features and hence introduce more challenges in constructing robust prediction models....

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Detalles Bibliográficos
Autores principales: Fu, Jie, Singhrao, Kamal, Zhong, Xinran, Gao, Yu, Qi, Sharon X., Yang, Yingli, Ruan, Dan, Lewis, John H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Scientific Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8377554/
https://www.ncbi.nlm.nih.gov/pubmed/34458648
http://dx.doi.org/10.1016/j.adro.2021.100746

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8377554/
https://www.ncbi.nlm.nih.gov/pubmed/34458648
http://dx.doi.org/10.1016/j.adro.2021.100746

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