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Ish: Deep learning-based postoperative glioblastoma segmentation and extent of resection evaluation: Development, external validation, and model comparison
nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation
Fabian Isensee, Paul F. Jaeger, Simon A. A. Kohl +2
MaqolaOchiq kirish202012 iqtibosABIThe Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository
Kenneth Clark, Bruce A. Vendt, Kirk Smith +9
MaqolaOchiq kirish20138 iqtibosABIThe 2021 WHO Classification of Tumors of the Central Nervous System: a summary
David N. Louis, Arie Perry, Pieter Wesseling +10
Sharh maqolaOchiq kirish20218 iqtibosABIAdvancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features
Spyridon Bakas, Hamed Akbari, Aristeidis Sotiras +6
MaqolaOchiq kirish20174 iqtibosABIEfficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation
Konstantinos Kamnitsas, Christian Ledig, Virginia Newcombe +5
MaqolaOchiq kirish20163 iqtibosABIModified Criteria for Radiographic Response Assessment in Glioblastoma Clinical Trials
Benjamin M. Ellingson, Patrick Y. Wen, Timothy F. Cloughesy
Sharh maqolaOchiq kirish20173 iqtibosABIPreoperative Brain Tumor Imaging: Models and Software for Segmentation and Standardized Reporting
David Bouget, André Pedersen, Asgeir Store Jakola +27
MaqolaOchiq kirish20222 iqtibosABI