MC-GenRef: Annotation-free mammography microcalcification segmentation with generative posterior refinement
Microcalcification (MC) analysis is clinically important in screening mammography because clustered puncta can be an early sign of malignancy, yet dense MC segmentation remains challenging: targets are extremely small and sparse, dense pixel-level labels are expensive and ambiguous, and cross-site shift often induces texture-driven false positives and missed puncta in dense tissue. We propose MC-GenRef, a real dense-label-free framework that combines high-fidelity synthetic supervision with test-time generative posterior refinement (TT-GPR). During training, real negative mammogram patches are used as backgrounds, and physically plausible MC patterns are injected through a lightweight ima...
| Authors | Hyunwoo Cho, Yeeun Kwon, Min Jung Kim et al. |
|---|---|
| Primary category | eess.IV |
| Published | 6 April 2026 |
| Last updated at source | 6 April 2026 |
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