arXiv:2506.14318v4 Announce Type: replace-cross 
Abstract: Accurate segmentation and classification of brain tumors from Magnetic Resonance Imaging (MRI) remain key challenges in medical image analysis, primarily due to the lack of high-quality, balanced, and diverse datasets with expert annotations. In this work, we address this gap by introducing BRISC, a dataset designed for brain tumor segmentation and classification tasks, featuring high-resolution segmentation masks. The dataset comprises 6,000 contrast-enhanced T1-weighted MRI scans, which were collated from multiple public datasets that lacked segmentation labels. Our primary contribution is the subsequent expert annotation of these images, performed by certified radiologists and physicians. It includes three major tumor types, namely glioma, meningioma, and pituitary, as well as non-tumorous cases. Each sample includes high-resolution labels and is categorized across axial, sagittal, and coronal imaging planes to facilitate robust model development and cross-view generalization. To demonstrate the utility of the dataset, we provide benchmark results for both tasks using standard deep learning models. The BRISC dataset is made publicly available. datasetlink: Kaggle (https://www.kaggle.com/datasets/briscdataset/brisc2025/), Figshare (https://doi.org/10.6084/m9.figshare.30533120), Zenodo (https://doi.org/10.5281/zenodo.17524350)

تقديم مجموعة بيانات BRISC يمثل تقدمًا كبيرًا في مجال تحليل الصور الطبية، خاصةً في مجال تقسيم وتصنيف أورام الدماغ. من خلال توفير صور الرنين المغناطيسي المعلّمة عالية الجودة، تسد هذه المجموعة الفجوة الحرجة في الموارد الحالية، مما يمكّن الباحثين من تطوير أدوات تشخيصية أكثر دقة. هذا أمر حاسم لتحسين نتائج المرضى وتعزيز الفهم العام لأورام الدماغ.

La introducción del conjunto de datos BRISC marca un avance significativo en el campo del análisis de imágenes médicas, especialmente para la segmentación y clasificación de tumores cerebrales. Al proporcionar imágenes de MRI anotadas de alta calidad, este conjunto de datos aborda una brecha crítica en los recursos existentes, permitiendo a los investigadores desarrollar herramientas de diagnóstico más precisas. Esto es crucial para mejorar los resultados de los pacientes y avanzar en la comprensión general de los tumores cerebrales.

L'introduction du jeu de données BRISC représente une avancée significative dans le domaine de l'analyse d'images médicales, en particulier pour la segmentation et la classification des tumeurs cérébrales. En fournissant des images IRM annotées de haute qualité, ce jeu de données comble une lacune critique dans les ressources existantes, permettant aux chercheurs de développer des outils de diagnostic plus précis. Cela est crucial pour améliorer les résultats des patients et faire progresser la compréhension globale des tumeurs cérébrales.

The introduction of the BRISC dataset marks a significant advancement in the field of medical image analysis, particularly for brain tumor segmentation and classification. By providing high-quality, annotated MRI images, this dataset addresses a critical gap in existing resources, enabling researchers to develop more accurate diagnostic tools. This is crucial for improving patient outcomes and advancing the overall understanding of brain tumors.

BRISC: Annotated Dataset for Brain Tumor Segmentation and Classification

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