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Article

IDH1 mutation prediction using MR-based radiomics in glioblastoma: comparison between manual and fully automated deep learning-based approach of tumor segmentation.

European journal of radiology - 1 Jul 2020

Choi Yangsean, Nam Yoonho, Lee Youn Soo, Kim Jiwoong, Ahn Kook-Jin, Jang Jinhee, Shin Na-Young, Kim Bum-Soo, Jeon Sin-Soo

Abstract excerpt

PURPOSE: This study aimed to determine whether MR-based radiomics of glioblastoma can predict the isocitrate dehydrogenase-1 (IDH1) mutation status and compare predictive performances between manual and fully automatic deep-learning segmentations. METHOD: Forty-five glioblastoma patients with pretreatment T2-weighted MRIs were retrospectively evaluated. Manual segmentations of glioblastoma and peri-tumoral edema...

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Identifiers

PMID: 32417712
DOI: 10.1016/j.ejrad.2020.109031

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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