Generating Synthetic X-ray Image Methods for Vascular Interventional Surgery

Abstract

The scarcity and difficulty in acquiring vascular interventional surgery data have hindered the development of this field. To address this challenge, we propose a novel application of the Deep Digitally Reconstructed Radiographs(DeepDRR) method for synthesizing X-ray images of vascular interventional surgery with guidewires. By merging predefined-shaped guidewires with computed tomography(CT) scan images, composite CT images containing guidewires can be obtained. The DeepDRR model is then used to project these images, producing corresponding X-ray images. Experimental results demonstrate that the synthesized X-ray images with guidewires possess a certain degree of realism and can be generated at a relatively fast speed, achieving 2.69 frames per second (FPS). This study establishes a pipeline for synthesizing vascular interventional images, laying a foundation for future research. This will provide high-quality and diverse data support for the development of vascular interventional surgery robots and promote further advancements in this field.