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A method for coronary bifurcation centerline reconstruction from angiographic images based on focalization optimization

机译:基于聚焦优化的血管造影图像冠状动脉分叉中心线重建方法

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A method for the reconstruction of a vessel centerline from angiographic images is outlined in this work. A typical coronary artery segment with bifurcations was emulated with a 3D printed static phantom and several angiograms were acquired at various angular positions on the C-Arm. The effectiveness of the reconstruction turned out to be largely influenced by the intrinsic parameters of the angiographic system, particularly the homogeneous coordinates system scaling factor λ. Therefore, recourse was made to a heuristic optimization method to estimate the optimal value of λ for each view. We measured the reliability of the reconstruction method by varying the fitness function of the optimization step and measuring the distances of 8 test points in comparison to the corresponding points identified in the μCT centerline. Preliminary results showed that, with an adequate number of views, the adoption of the optimal fitness function allowed the median distance error to be decreased below the acceptance threshold of 10%. As expected, the reliability of the method is improved by increasing the number of processed views.
机译:在这项工作中概述了一种从血管造影图像重建血管中心线的方法。用3D打印的静态体模模拟具有分叉的典型冠状动脉节段,并在C型臂上的各个角度位置获取几张血管造影照片。事实证明,重建的有效性很大程度上受到血管造影系统固有参数的影响,特别是均质坐标系比例因子λ。因此,求助于启发式优化方法以估计每个视图的最优λ值。我们通过改变优化步骤的适应度函数并测量8个测试点与μCT中心线中标识的对应点的距离,来测量重构方法的可靠性。初步结果表明,在有足够数量的视图的情况下,采用最佳适应度函数可使距离中位数误差减小到可接受阈值10%以下。如预期的那样,通过增加已处理视图的数量来提高该方法的可靠性。

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