Ordered multi-path propagation for vessel centerline extraction
Ordered multi-path propagation for vessel centerline extraction
复制标题
用于血管中心线提取的有序多路径传播
DOI：
10.1088/1361-6560/ac0d8e
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发表时间：
2021-06
期刊：
影响因子：
--
通讯作者：
Jian Yang
中科院分区：
文献类型：
--
作者：
Tao Han;Danni Ai;Ruirui An;Jingfan Fan;Hong Song;Yining Wang;Jian Yang
血管中心线的提取是冠状动脉疾病诊断中血管结构分析的基础。然而，由于图像噪声、对比度差和血管结构的复杂性，完整和连续的中心线提取仍然是一项具有挑战性的任务。因此，提出了一种用于自动提取血管中心线的迭代多路径搜索框架。首先，检测血管结构的种子点并按置信度排序。利用有序种子点，通过波前多路径传播和累积投票搜索多分叉中心线。最后，在关键点检测的基础上，通过波前传播对中心线进行分段延拓。后两个步骤交替执行，以获得最终的中心线结果。所提出的方法进行了定性和定量评价1260合成图像和50临床血管造影图像。实验结果表明，该方法对血管造影图像具有较高的F1值（87.8% ± 2.7%），能够准确、连续地提取血管中心线。
Vessel centerline extraction from x-ray angiography images is essential for vessel structure analysis in the diagnosis of coronary artery disease. However, complete and continuous centerline extraction remains a challenging task due to image noise, poor contrast, and complexity of vessel structure. Thus, an iterative multi-path search framework for automatic vessel centerline extraction is proposed. First, the seed points of the vessel structure are detected and sorted by confidence. With the ordered seed points, multi-bifurcation centerline is searched through multi-path propagation of wavefront and accumulated voting. Finally, the centerline is further extended piecewise by wavefront propagation on the basis of keypoint detection. The latter two steps are performed alternately to obtain the final centerline result. The proposed method is qualitatively and quantitatively evaluated on 1260 synthetic images and 50 clinical angiography images. The results demonstrate that our method has a high F1 score of 87.8% ± 2.7% for the angiography images and achieves accurate and continuous results of vessel centerline extraction.
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影响因子：
37.8
作者：
Roger VL;Go AS;Lloyd-Jones DM;Benjamin EJ;Berry JD;Borden WB;Bravata DM;Dai S;Ford ES;Fox CS;Fullerton HJ;Gillespie C;Hailpern SM;Heit JA;Howard VJ;Kissela BM;Kittner SJ;Lackland DT;Lichtman JH;Lisabeth LD;Makuc DM;Marcus GM;Marelli A;Matchar DB;Moy CS;Mozaffarian D;Mussolino ME;Nichol G;Paynter NP;Soliman EZ;Sorlie PD;Sotoodehnia N;Turan TN;Virani SS;Wong ND;Woo D;Turner MB;American Heart Association Statistics Committee and Stroke Statistics Subcommittee
通讯作者：
American Heart Association Statistics Committee and Stroke Statistics Subcommittee
DOI：
10.1109/tpami.2011.267
发表时间：
2012-10
影响因子：
23.6
作者：
V. Kaul;A. Yezzi;Y. Tsai
通讯作者：
V. Kaul;A. Yezzi;Y. Tsai
DOI：
10.1007/978-3-319-78199-0_33
发表时间：
2017-10
期刊：
ArXiv
影响因子：
--
作者：
E. Cohen;L. Cohen;T. Deffieux;M. Tanter
通讯作者：
E. Cohen;L. Cohen;T. Deffieux;M. Tanter
DOI：
10.1109/tcsvt.2019.2892986
发表时间：
2020-02
影响因子：
8.4
作者：
Huihui Fang;Danni Ai;Weijian Cong;Siyuan Yang;Jianjun Zhu;Yong Huang;Hong Song;Yongtian Wang;Jian Yang
通讯作者：
Huihui Fang;Danni Ai;Weijian Cong;Siyuan Yang;Jianjun Zhu;Yong Huang;Hong Song;Yongtian Wang;Jian Yang
影响因子：
3.2
作者：
Fazlali, Hamid R.;Karimi, Nader;Najarian, Kayvan
通讯作者：
Najarian, Kayvan