Structured Reporting

Structured reporting in radiology aims to transform free-text medical reports into standardized, machine-readable formats to improve efficiency and data analysis. Current research heavily utilizes large language models (LLMs), particularly transformer-based architectures, to automatically extract information from free-text reports and populate structured templates, often incorporating techniques like template-constrained decoding and visual question answering (VQA). This automated approach holds significant promise for streamlining clinical workflows, facilitating large-scale data analysis for research and improving the accuracy and consistency of medical record-keeping.