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The Río Hortega University Hospital Glioblastoma dataset: A comprehensive collection of preoperative, early postoperative and recurrence MRI scans (RHUH-GBM).
Cepeda, Santiago; García-García, Sergio; Arrese, Ignacio; Herrero, Francisco; Escudero, Trinidad; Zamora, Tomás; Sarabia, Rosario.
Afiliação
  • Cepeda S; Department of Neurosurgery, Río Hortega University Hospital, Dulzaina 2, 47012 Valladolid, Spain.
  • García-García S; Department of Neurosurgery, Río Hortega University Hospital, Dulzaina 2, 47012 Valladolid, Spain.
  • Arrese I; Department of Neurosurgery, Río Hortega University Hospital, Dulzaina 2, 47012 Valladolid, Spain.
  • Herrero F; Department of Radiology, Río Hortega University Hospital, Dulzaina 2, 47012 Valladolid, Spain.
  • Escudero T; Department of Radiology, Río Hortega University Hospital, Dulzaina 2, 47012 Valladolid, Spain.
  • Zamora T; Department of Pathology, Río Hortega University Hospital, Dulzaina 2, 47012 Valladolid, Spain.
  • Sarabia R; Department of Neurosurgery, Río Hortega University Hospital, Dulzaina 2, 47012 Valladolid, Spain.
Data Brief ; 50: 109617, 2023 Oct.
Article em En | MEDLINE | ID: mdl-37808543
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 "Río 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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Data Brief Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Espanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Data Brief Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Espanha