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Automated connectivity-based groupwise cortical atlas generation: Application to data of neurosurgical patients with brain tumors for cortical parcellation prediction.

, , , , , , , , , , , and . ISBI, page 774-777. IEEE, (2017)

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PyRaDiSe: A Python package for DICOM-RT-based auto-segmentation pipeline construction and DICOM-RT data conversion., , , , , , and . Comput. Methods Programs Biomed., (April 2023)Deep Learning Versus Classical Regression for Brain Tumor Patient Survival Prediction., , , , , , and . BrainLes@MICCAI (2), volume 11384 of Lecture Notes in Computer Science, page 429-440. Springer, (2018)Towards MRI Progression Features for Glioblastoma Patients: From Automated Volumetry and Classical Radiomics to Deep Feature Learning., , , , , and . MLCN/RNO-AI@MICCAI, volume 12449 of Lecture Notes in Computer Science, page 129-138. Springer, (2020)Advanced Machine Learning Technologies for Robust Longitudinal Radiomics and Response Assessment in Glioblastoma Multiforme.. University of Bern, Switzerland, (2021)base-search.net (ftunivbern:oai:boris.unibe.ch:169142).Fast and uncertainty-aware cerebral cortex morphometry estimation using random forest regression., , , and . ISBI, page 1052-1055. IEEE, (2018)The MICCAI Hackathon on reproducibility, diversity, and selection of papers at the MICCAI conference., , , , , , , , , and 5 other author(s). CoRR, (2021)Overall Survival Prediction for Glioblastoma on Pre-treatment MRI Using Robust Radiomics and Priors., , , and . BrainLes@MICCAI (1), volume 12658 of Lecture Notes in Computer Science, page 307-317. Springer, (2020)