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Tumor segmentation is a particularly challenging task in high-grade gliomas (HGGs), as they are among the most heterogeneous tumors in oncology. An accurate delineation of the lesion and its main subcomponents contributes to optimal treatment planning, prognosis and follow-up. Conventional MRI (cMRI) is the imaging modality of choice for manual segmentation, and is also considered in the vast majority of automated segmentation studies. Advanced MRI modalities such as perfusion-weighted imagingdoi:10.1016/j.nicl.2016.09.021 pmid:27812502 pmcid:PMC5079350 fatcat:vnicyvw34bgtjc6yb3eegn4gzi