3 papers
cs.CV2025
More performant and scalable: Rethinking contrastive vision-language pre-training of radiology in the LLM era
Yingtai Li, Haoran Lai, Xiaoqian Zhou +4
The emergence of Large Language Models (LLMs) presents unprecedented opportunities to revolutionize medical contrastive vision-language pre-training. In this paper, we show how LLM…
cs.CV2025
SimCroP: Radiograph Representation Learning with Similarity-driven Cross-granularity Pre-training
Rongsheng Wang, Fenghe Tang, Qingsong Yao +8
Medical vision-language pre-training shows great potential in learning representative features from massive paired radiographs and reports. However, in computed tomography (CT) sca…
cs.CV2024
CARZero: Cross-Attention Alignment for Radiology Zero-Shot Classification
Haoran Lai, Qingsong Yao, Zihang Jiang +4
The advancement of Zero-Shot Learning in the medical domain has been driven forward by using pre-trained models on large-scale image-text pairs, focusing on image-text alignment. H…