Topology Optimization Using Multiple-Possibility Fusion for Vasculature Extraction
Topology Optimization Using Multiple-Possibility Fusion for Vasculature Extraction
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DOI：
10.1109/tcsvt.2019.2892986
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发表时间：
2020-02
影响因子：
8.4
通讯作者：
Huihui Fang;Danni Ai;Weijian Cong;Siyuan Yang;Jianjun Zhu;Yong Huang;Hong Song;Yongtian Wang;Jian Yang
中科院分区：
文献类型：
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作者：
Huihui Fang;Danni Ai;Weijian Cong;Siyuan Yang;Jianjun Zhu;Yong Huang;Hong Song;Yongtian Wang;Jian Yang
血管中心线的提取在血管疾病的计算机辅助诊断中起着重要的作用。为了解决噪声和不一致的血管灌注不均匀的常见问题，本文提出了一种自动框架，准确的血管中心线提取血管造影片，使用多概率融合的拓扑优化。在这个框架中，首先使用基于学习的方法分割血管区域。然后，通过迭代滤波和多方向索引非极大值抑制得到初始中心线。通过间隙填充实现拓扑优化。利用血管的初始中心线、纹理和方向的信息构建连接概率图。最短路径跟踪被用来搜索初始中心线中的间隙周围的最优连接。使用模拟和临床冠状动脉造影评估建议的框架。实验结果表明，该方法对12幅临床血管造影图像中的血管中心线提取的F1值为97.28% ± 1.2%。实验结果表明，该方法可以从血管图像中提取出完整、准确的血管中心线，并可用于修复道路、视网膜血管等其他血管结构的缺损。这使我们的方法在分析非线性结构中具有很大的潜力。
Vascular centerline extraction from angiography images plays an important role in computer-aided diagnosis of vascular disease. To solve the common problems related to noise and inconsistent vasculatures from uneven perfusion, this paper proposes an automatic framework for accurate vascular centerline extraction from angiograms that uses multi-probability fusion-based topology optimization. In this framework, vascular region is first segmented using a learning-based method. Then, initial centerlines are obtained by applying iterative filtering operation and multi-direction indexed non-maximum suppression. Topology optimization is achieved by gap filling. A connection probability map is constructed utilizing the information of initial centerlines, texture, and orientation of vasculatures. Shortest path tracking is employed to search for optimal connections around gaps in the initial centerlines. The proposed framework is evaluated using simulative and clinical coronary angiographies. The experimental results demonstrate that the proposed method can extract centerlines with F1 score of 97.28% ± 1.2% for vasculatures in 12 clinical angiographic images. It is evident that the proposed method can extract complete and accurate vascular centerlines from angiograms and can be used to repair gaps in other filamentary structures, such as roads and retinal blood vessels. This endows our method a great potential in the analysis of filamentary structures.