Noninvasive Classification of Glioma Subtypes Using Multiparametric MRI to Improve Deep Learning

Background: Deep learning (DL) methods can noninvasively predict glioma subtypes; however, there is no set paradigm for the selection of network structures and input data, including the image combination method, image processing strategy, type of numeric data, and others. Purpose: To compare differe...

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Detalles Bibliográficos
Autores principales: Xiong, Diaohan, Ren, Xinying, Huang, Weiting, Wang, Rui, Ma, Laiyang, Gan, Tiejun, Ai, Kai, Wen, Tao, Li, Yujing, Wang, Pengfei, Zhang, Peng, Zhang, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9776470/
https://www.ncbi.nlm.nih.gov/pubmed/36553070
http://dx.doi.org/10.3390/diagnostics12123063

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9776470/
https://www.ncbi.nlm.nih.gov/pubmed/36553070
http://dx.doi.org/10.3390/diagnostics12123063

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