CT2Rep: Automated Radiology Report Generation for 3D Medical Imaging

arXiv:2403.06801v1 Announce Type: cross
Abstract: Medical imaging plays a crucial role in diagnosis, with radiology reports serving as vital documentation. Automating report generation has emerged as a critical need to alleviate the workload of radiologists. While machine learning has facilitated report generation for 2D medical imaging, extending this to 3D has been unexplored due to computational complexity and data scarcity. We introduce the first method to generate radiology reports for 3D medical imaging, specifically targeting chest CT volumes. Given the …

arxiv automated cs.cv eess.iv imaging medical medical imaging radiology report type