Deep Learning based Radiomics (DLR) and its usage in noninvasive IDH1 prediction for low grade glioma

Deep learning-based radiomics (DLR) was developed to extract deep information from multiple modalities of magnetic resonance (MR) images. The performance of DLR for predicting the mutation status of isocitrate dehydrogenase 1 (IDH1) was validated in a dataset of 151 patients with low-grade glioma. A...

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Detalles Bibliográficos
Autores principales: Li, Zeju, Wang, Yuanyuan, Yu, Jinhua, Guo, Yi, Cao, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5511238/
https://www.ncbi.nlm.nih.gov/pubmed/28710497
http://dx.doi.org/10.1038/s41598-017-05848-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5511238/
https://www.ncbi.nlm.nih.gov/pubmed/28710497
http://dx.doi.org/10.1038/s41598-017-05848-2

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