Large Model driven Radiology Report Generation with Clinical Quality Reinforcement Learning

arXiv:2403.06728v1 Announce Type: new
Abstract: Radiology report generation (RRG) has attracted significant attention due to its potential to reduce the workload of radiologists. Current RRG approaches are still unsatisfactory against clinical standards. This paper introduces a novel RRG method, \textbf{LM-RRG}, that integrates large models (LMs) with clinical quality reinforcement learning to generate accurate and comprehensive chest X-ray radiology reports. Our method first designs a large language model driven feature extractor to analyze and interpret different regions of the chest X-ray …

abstract arxiv attention clinical cs.cv current large models lms novel paper quality radiology reduce reinforcement reinforcement learning report standards type