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Generating Synthetic X-ray Image Methods for Vascular Interventional Surgery

Bingzhi Shen, Shuxiang Guo, Chuqiao Lyu, Yonggan Yan, Duohao Zhao, Zhijun Lin, Bin Wang, Mingchao Ding

发表年份
2024
引用次数
4

摘要

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.

关键词

Computer scienceImage (mathematics)Artificial intelligenceComputer visionMedicineRadiology

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