755 citations · 1.1k across the 14 of their papers we have counts for
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RoentGen: Vision-Language Foundation Model for Chest X-ray Generation
Pierre Chambon, Christian Bluethgen, Jean-Benoit Delbrouck +7
Multimodal models trained on large natural image-text pair datasets have exhibited astounding abilities in generating high-quality images. Medical imaging data is fundamentally dif…
Toward expanding the scope of radiology report summarization to multiple anatomies and modalities
Zhihong Chen, Maya Varma, Xiang Wan +2
Radiology report summarization (RRS) is a growing area of research. Given the Findings section of a radiology report, the goal is to generate a summary (called an Impression sectio…
Improving the Factual Correctness of Radiology Report Generation with Semantic Rewards
Jean-Benoit Delbrouck, Pierre Chambon, Christian Bluethgen +3
Neural image-to-text radiology report generation systems offer the potential to improve radiology reporting by reducing the repetitive process of report drafting and identifying po…
Adapting Pretrained Vision-Language Foundational Models to Medical Imaging Domains
Pierre Chambon, Christian Bluethgen, Curtis P. Langlotz +1
Multi-modal foundation models are typically trained on millions of pairs of natural images and text captions, frequently obtained through web-crawling approaches. Although such mod…