谷歌浏览器插件
订阅小程序
在清言上使用

Vessel Segmentation of X-Ray Coronary Angiographic Image Sequence

IEEE Transactions on Biomedical Engineering(2020)

引用 22|浏览20
暂无评分
摘要
Objective: To facilitate the analysis and diagnosis of X-ray coronary angiography in interventional surgery, it is necessary to extract vessel from X-ray coronary angiography. However, vessel images of angiography suffer from low quality with large artefacts, which challenges the existing vascular technology. Methods: In this paper, we propose a avessel framework to detect vessels and segment vessels in angiographic vessel data. In this framework, we develop a new matrix decomposition model with gradient sparse in the tensor representation. Then, the energy function with the input of the hierarchical vessel is used in vessel detection and vessel segmentation. Results: Through experiments conducted on angiographic data, we have demonstrated the good performance of the proposed method in removing background structure. Conclusion: We evaluated our method for vessel detection and segmentation in different clinical settings, including LAO/RAO with cranial and caudal angulation, and showed its competitive results compared with eight state-of-the-art methods in terms of extensive qualitative and quantitative evaluation. Significance: Our method can remove a large number of background artefacts and obtain a better vascular structure, which has contributed to the clinical diagnosis of coronary artery diseases.
更多
查看译文
关键词
X-ray angiograms,matrix decomposition model,Laplacian regularization,Hessian enhancement,hierarchical vessel,vessel video segmentation,energy optimization,vessel image
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要