Segmentation Labels for the Pre-operative Scans of the TCGA-GBM collection

Special Instruction:

The dataset should not be listed until a related manuscript is published.

Description

This data container describes both computer-aided and manually-corrected segmentation labels for the pre-operative multi-institutional scans of The Cancer Genome Atlas (TCGA) Glioblastoma Multiforme (GBM) collection, publicly available in The Cancer Imaging Archive (TCIA), coupled with their skull-stripped and co-registered multimodal (i.e. T1, T1-Gd, T2, T2-FLAIR) magnetic resonance imaging (MRI) volumes in NIFTI format. Pre-operative multimodal MRI scans were identified in the TCGA-GBM collection, via radiological assessment. These scans were initially skull-stripped and co-registered, before their tumor segmentation labels were produced by an automated hybrid generative-discriminative method, ranked first during the International multimodal BRAin Tumor Segmentation challenge (BRATS 2015). The resulted labels were revised, and any label misclassifications were manually corrected, by an expert Neuroradiologist. The resulted labels, both computer-aided and manually-revised, enable quantitative computational and clinical studies without the need to repeat manual annotations and whilst allowing for comparison across studies, as well as they can serve as a performance evaluation manually-annotated gold standard set of labels for computational challenges.

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• Original DICOM Image Data (xx GB)
• Processed NIFTI images + Segmentations (xx MB)