Disclosure: We created and published this dataset.
New Open-Access Benchmark: Hierarchical segmentation of vascular fibrosis in computational pathology.
The Core Challenge:
Segmenting the vascular wall is well-defined (baseline UNet DSC ≈ 0.80; inter-expert DSC ≈ 0.95). However, segmenting the intramural fibrotic microstructure remains an open problem. Due to its diffuse and heterogeneous nature, our baseline MONAI UNet achieves a DSC of only ~0.12 on fibrosis, while human inter-expert agreement averages ~0.61 DSC.
Dataset Specifications:
🔬 Scale: 705 high-resolution micrographs (1534×780 px, 0.252 μm/px), Picro-Mallory stain.
🏷️ Annotations: ROI + dual independent expert masks (vascular wall + fibrosis).
⚠️ Hierarchical Constraint: Fibrosis masks must be strictly spatially contained within the vascular wall.
🛡️ Robust Benchmarking: No color normalization applied; native aspect ratios preserved; strict animal-level 5-fold CV splits provided to prevent data leakage.
📄 Read the Data Descriptor: https://doi.org/10.1038/s41597-026-08214-y
🗂️ Access the Dataset: https://doi.org/10.6084/m9.figshare.31386748
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