BRISC: Annotated Dataset for Brain Tumor Segmentation and Classification
Iran University of Science and Technology · University of Shahrood · +2 more institutions
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…
Citation impact
- FWCI
- 153.30
- Percentile
- 100%
- References
- 29
Authors
7Topics & keywords
- Segmentation
- Benchmark (surveying)
- Pattern recognition (psychology)
- Annotation
- Key (lock)
- Deep learning
- Magnetic resonance imaging