MGRegBench: A Novel Benchmark Dataset with Anatomical Landmarks for Mammography Image Registration 文章

arXiv:2512.17605v2 Announce Type: replace Abstract: Robust mammography registration is essential for clinically relevant applications like tracking disease progression in breast tissue. However, progress has been limited by the absence of transparent public datasets and reproducible standardized benchmarks. Existing studies are often not directly comparable, as they use private data and inconsistent evaluation frameworks. To address this, we present MGRegBench, a patient-disjoint, leakage-controlled evaluation protocol for mammography registration, comprising over 5,000 image pairs, each with a breast segmentation mask, and 100 pairs with manually annotated anatomical landmarks, plus standardized train/evaluation splits and ready-to-run baselines.