MedSyn: Text-guided Anatomy-aware Synthesis of High-Fidelity 3D CT Images

arXiv:2310.03559v5 Announce Type: replace-cross
Abstract: This paper introduces an innovative methodology for producing high-quality 3D lung CT images guided by textual information. While diffusion-based generative models are increasingly used in medical imaging, current state-of-the-art approaches are limited to low-resolution outputs and underutilize radiology reports' abundant information. The radiology reports can enhance the generation process by providing additional guidance and offering fine-grained control over the synthesis of images. Nevertheless, expanding text-guided generation to high-resolution 3D images poses significant memory and anatomical …

abstract art arxiv cs.cv current diffusion eess.iv fidelity generative generative models images imaging information low medical medical imaging methodology paper quality radiology replace reports resolution state synthesis text textual type while