Glioblastoma, a highly aggressive primary brain tumor, is associated with poor patient outcomes. Although magnetic resonance imaging (MRI) plays a critical role in diagnosing, characterizing, and forecasting glioblastoma progression, public MRI repositories present significant drawbacks, including insufficient postoperative and follow-up studies as well as expert tumor segmentations. To address these issues, we present the "R\'io Hortega University Hospital Glioblastoma Dataset (RHUH-GBM)," a collection of multiparametric MRI images, volumetric assessments, molecular data, and survival details for glioblastoma patients who underwent total or near-total enhancing tumor resection. The dataset features expert-corrected segmentations of tumor subregions, offering valuable ground truth data for developing algorithms for postoperative and follow-up MRI scans. The public release of the RHUH-GBM dataset significantly contributes to glioblastoma research, enabling the scientific community to study recurrence patterns and develop new diagnostic and prognostic models. This may result in more personalized, effective treatments and ultimately improved patient outcomes.

通过提供精确的分割肿瘤区域作为数据集，以便开发出术后和随访MRI扫描算法，RHUH-GBM数据集显著促进了胶质母细胞瘤研究的发展，为研究胶质母细胞瘤复发模式、开发新的诊断和预后模型提供了宝贵的数据帮助，最终带来更加个性化、有效的治疗，并提高患者的预后。

The Río Hortega University Hospital Glioblastoma dataset: a
  comprehensive collection of preoperative, early postoperative and recurrence
  MRI scans (RHUH-GBM)

Rio Hortega大学医院Glioblastoma数据集：术前、术后早期及复发期MRI扫描的全面收集（RHUH-GBM）