biodatlab/Med-ReasonSeg

Med-ReasonSeg Med-ReasonSeg is a large-scale reasoning segmentation dataset containing 539,383 image–mask–Q&A triplets derived from 90,021 distinct scans across 9 imaging modalities from 16 publicly available biomedical image segmentation datasets. The dataset was constructed and verified via a two-stage LLM pipeline to ensure logical fidelity and reduce hallucinations. It was designed and used to train MedFuse-Seg (MICCAI 2026), a reasoning-driven medical image segmentation… See the full description on the dataset page: https://huggingface.co/datasets/biodatlab/Med-ReasonSeg.

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