A Hessian-based filter for vascular segmentation of noisy hepatic CT scans
A Hessian-based filter for vascular segmentation of noisy hepatic CT scans
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DOI：
10.1007/s11548-011-0640-y
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发表时间：
2012-03-01
影响因子：
3
通讯作者：
Hori, Masatoshi
中科院分区：
文献类型：
--
作者：
Foruzan, Amir H.;Zoroofi, Reza A.;Hori, Masatoshi
目的 管状结构的提取和增强在图像处理应用中非常重要，特别是在肝脏 CT 扫描分析中，其中需要勾画血管结构以进行手术规划。门静脉横截面具有圆形或椭圆形形状，因此算法必须适应这两种形状。开发了一种基于中轴点的血管分割方法，并在CT图像中的门静脉上进行了测试。方法开发了中轴增强滤波器。考虑一条穿过管内点并与管边缘相交的线。如果该点位于中轴上，则该点在线方向上到管边缘的距离将相等。该特征被用于多尺度框架中来识别肝血管。动态阈值用于降低噪声敏感性。 Pock 等人引入的各向同性系数。用于减少滤波器对不对称横截面的响应。结果使用 2D/3D 和合成/临床数据集对所提出的方法进行了定量和定性评估。与其他中轴增强方法相比，我们的方法在低分辨率 CT 图像中产生更好的结果。在标准差等于0.3的噪声图像中，所提出的方法对中轴的检测率比现有方法高68%。结论开发并测试了一种新的基于Hessian的中轴血管分割方法。与以前的方法相比，该方法产生了更好的结果。这种新方法具有中轴增强的许多应用潜力。
Purpose Extraction and enhancement of tubular structures are important in image processing applications, especially in the analysis of liver CT scans where delineation of vascular structures is needed for surgical planning. Portal vein cross-sections have circular or elliptical shapes, so an algorithm must accommodate both. A vessel segmentation method based on medial-axis points was developed and tested on portal veins in CT images.Methods A medial-axis enhancement filter was developed. Consider a line passing through a point inside a tube and intersecting the edges of the tube. If the point is located on the medial axis, the distance of the point in the direction of the line to the edges of the tube will be equal. This feature was employed in a multi-scale framework to identify liver vessels. Dynamic thresholding was used to reduce noise sensitivity. The isotropic coefficient introduced by Pock et al. was used to reduce the response of the filter for asymmetric cross-sections.Results Quantitative and qualitative evaluation of the proposed method were performed using both 2D/3D and synthetic/clinical datasets. Compared to other methods for medial-axis enhancement, our method produces better results in low-resolution CT images. Detection rate of the medial axis by the proposed method in a noisy image of standard deviation equal to 0.3 is 68% higher than prior methods.Conclusion A new Hessian-based method for medial axis vessel segmentation was developed and tested. This method produced superior results compared to prior methods. This new method has the potential for many applications of medial-axis enhancement.