Prediction of IDH and TERT promoter mutations in low-grade glioma from magnetic resonance images using a convolutional neural network

Identification of genotypes is crucial for treatment of glioma. Here, we developed a method to predict tumor genotypes using a pretrained convolutional neural network (CNN) from magnetic resonance (MR) images and compared the accuracy to that of a diagnosis based on conventional radiomic features an...

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Detalles Bibliográficos
Autores principales: Fukuma, Ryohei, Yanagisawa, Takufumi, Kinoshita, Manabu, Shinozaki, Takashi, Arita, Hideyuki, Kawaguchi, Atsushi, Takahashi, Masamichi, Narita, Yoshitaka, Terakawa, Yuzo, Tsuyuguchi, Naohiro, Okita, Yoshiko, Nonaka, Masahiro, Moriuchi, Shusuke, Takagaki, Masatoshi, Fujimoto, Yasunori, Fukai, Junya, Izumoto, Shuichi, Ishibashi, Kenichi, Nakajima, Yoshikazu, Shofuda, Tomoko, Kanematsu, Daisuke, Yoshioka, Ema, Kodama, Yoshinori, Mano, Masayuki, Mori, Kanji, Ichimura, Koichi, Kanemura, Yonehiro, Kishima, Haruhiko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6937237/
https://www.ncbi.nlm.nih.gov/pubmed/31889117
http://dx.doi.org/10.1038/s41598-019-56767-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6937237/
https://www.ncbi.nlm.nih.gov/pubmed/31889117
http://dx.doi.org/10.1038/s41598-019-56767-3

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