"CT-MRI Glioblastoma Multimodal Benchmark Dataset "

"Multimodal medical imaging is essential for comprehensive analysis of glioblastoma, offering complementary structural and pathological information through different imaging modalities. However, the availability of paired Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) data for the same patient remains limited, posing a significant challenge for multimodal learning and fusion-based approaches. In this work, we present a curated multimodal glioblastoma dataset comprising CT and MRI scans of 50 patients, sourced from publicly available cases on Radiopaedia. The dataset emphasizes patient-level pairing, ensuring the presence of both modalities for each subject. Careful selection and organization of cases enable reliable cross-modal analysis and facilitate the development of machine learning models for tumor detection, segmentation, and multimodal fusion. This dataset addresses a critical gap in accessible paired imaging resources and aims to support research in robust, data-driven glioblastoma characterization."