Radgen: A Cross-Modal Fusion System for Automated Radiology Report Generation

Automating radiology report generation can significantly reduce the workload of radiologists while improving the accuracy and consistency of clinical documentation. However, achieving optimal alignment between visual and textual representations in medical imaging remains a challenge. To address this, we demonstrate RadGen, a cross-modal fusion based system for automated medical report generation. RadGen uses MedCLIP as both a vision extractor and a retrieval mechanism to enhance the integration of imaging and textual data. By extracting features from retrieved reports and medical images through an attentionbased extraction module and integrating them with a fusion module, our system improves the coherence, accuracy, and clinical relevance of generated reports.