Learning Directional Semantic Transitions for Longitudinal Chest X-ray Analysis
Chest X-ray (CXR) interpretation often requires longitudinal comparison to assess disease progression. Existing approaches typically rely on temporal feature fusion or inter-study discrepancy modeling, yet remain limited in capturing subtle progression semantics and overlook the inherently directional nature of disease trajectories. In this paper, we propose ProTrans, a novel vision-language pretraining framework that formulates disease progression as a directional semantic transition between paired CXR studies. ProTrans leverages radiology reports to anchor individual CXR representations within interpretable disease states, and introduces a learnable progression feature map to explicitly...
| Authors | Zhangfeng Hu, Zefan Yang, Ge Wang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 14 June 2026 |
| Last updated at source | 14 June 2026 |
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