AI RESEARCH
Label-Efficient Cross-Modality Generalization for Liver Segmentation in Multi-Phase MRI
arXiv CS.CV
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ArXi:2510.04705v4 Announce Type: replace Accurate liver segmentation in multi-phase MRI is vital for liver fibrosis assessment, yet labeled data is often scarce and unevenly distributed across imaging modalities and vendor systems. We propose a label-efficient segmentation approach that promotes cross-modality generalization under real-world conditions, where GED4 hepatobiliary-phase annotations are limited, non-contrast sequences (T1WI, T2WI, DWI) are unlabeled, and spatial misalignment and missing phases are common.