Deep learning for glioblastoma segmentation using preoperative magnetic resonance imaging identifies volumetric features associated with survival.

Semi-automated segmentation of glioblastoma using a convolutional neural network trained on independent data is robust when applied to routine clinical data. The segmented volumes have prognostic significance.