SOURCE-LINKED INTELLIGENCE

Unified CT and MRI Pancreas Segmentation for Label-Efficient Cross-Modality Subregion Transfer

arXiv · AI, language, vision and robotics · article · Sep 11, 2026 · UTC

Robust medical image segmentation across imaging modalities is challenging because of large differences in appearance and intensity distributions. Models trained on a single modality often show substantial performance drops when applied to unseen domains. In this work, we develop a unified 3D pancreas segmentation framework that applies domain-adversarial learning to 4,604 heterogeneous CT and MRI scans to learn anatomical representations. A shared nnU-Net encoder-decoder is trained for whole-pancreas segmentation, with a latent domain discriminator encouraging CT-MRI feature alignment. The le

Read original source ↗ Open in workspace

recordType

paper

region

Global