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A vascular image registration method based on network structure and circuit simulation

机译:一种基于网络结构和电路仿真的血管图像登记方法

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Background Image registration is an important research topic in the field of image processing. Applying image registration to vascular image allows multiple images to be strengthened and fused, which has practical value in disease detection, clinical assisted therapy, etc. However, it is hard to register vascular structures with high noise and large difference in an efficient and effective method. Results Different from common image registration methods based on area or features, which were sensitive to distortion and uncertainty in vascular structure, we proposed a novel registration method based on network structure and circuit simulation. Vessel images were transformed to graph networks and segmented to branches to reduce the calculation complexity. Weighted graph networks were then converted to circuits, in which node voltages of the circuit reflecting the vessel structures were used for node registration. The experiments in the two-dimensional and three-dimensional simulation and clinical image sets showed the success of our proposed method in registration. Conclusions The proposed vascular image registration method based on network structure and circuit simulation is stable, fault tolerant and efficient, which is a useful complement to the current mainstream image registration methods.
机译:背景图像注册是图像处理领域的重要研究主题。将图像登记应用于血管图像允许加强和融合的多个图像,其具有疾病检测,临床辅助治疗等具有实用价值,但是,难以记录具有高噪声的血管结构和高效有效的方法差异很大。结果与基于区域或特征的常见图像配准方法不同,这对血管结构中的失真和不确定性敏感,我们提出了一种基于网络结构和电路仿真的新型登记方法。血管图像被转换为​​图形网络并分段为分支以降低计算复杂度。然后将加权图网络转换为电路,其中反射血管结构的电路的节点电压用于节点配准。二维和三维仿真和临床图像集中的实验表明我们提出的注册方法的成功。结论基于网络结构和电路仿真的提出的血管图像配准法是稳定的,容忍和高效,这是对当前主流图像配准方法的有用补充。

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