paper_authors: Elifnur Sunger, Beyza Kalkanli, Veysi Yildiz, Tales Imbiriba, Peter Campbell, Deniz Erdogmus
for: 用于计算管状物体的本地弯曲度
methods: 使用方向ional rate of change在Hessian矩阵的eigenvector上进行了本地弯曲度计算
results: 实验结果表明，Tubular Curvature Filter方法可以准确地计算管状物体任何点的本地弯曲度Abstract
Curvature estimation methods are important as they capture salient features for various applications in image processing, especially within medical domains where tortuosity of vascular structures is of significant interest. Existing methods based on centerline or skeleton curvature fail to capture curvature gradients across a rotating tubular structure. This paper presents a Tubular Curvature Filter method that locally calculates the acceleration of bundles of curves that traverse along the tubular object parallel to the centerline. This is achieved by examining the directional rate of change in the eigenvectors of the Hessian matrix of a tubular intensity function in space. This method implicitly calculates the local tubular curvature without the need to explicitly segment the tubular object. Experimental results demonstrate that the Tubular Curvature Filter method provides accurate estimates of local curvature at any point inside tubular structures.
摘要
CURVATURE 估计方法是重要的，因为它们捕捉了图像处理中的重要特征，特别是医疗领域中血管结构的折叠性是非常重要的。现有基于中心线或skeleton curvature的方法无法捕捉旋转管体结构中的曲线幅度跃变。本文介绍了一种管体曲线滤波器方法，它地方计算管体内部曲线的加速度，通过对管体内部曲线的平行方向进行方向差异率的检查，并通过计算管体内部曲线的HESSIAN矩阵的方向差异来计算本地管体曲线。这种方法不需要显式地分割管体对象，可以准确地估计管体内部任何点的曲线。实验结果表明，管体曲线滤波器方法可以准确地估计管体内部曲线的本地弯曲。