Almasi Sepideh, Xu Xiaoyin, Ben-Zvi Ayal, Lacoste Baptiste, Gu Chenghua, Miller Eric L
Dept. Electrical and Computer Engineering, Tufts University, Medford, MA, USA.
Dept. Radiology, Brigham and Women's Hospital, Boston, MA, USA.
Med Image Anal. 2015 Feb;20(1):208-23. doi: 10.1016/j.media.2014.11.007. Epub 2014 Nov 28.
A novel approach to determine the global topological structure of a microvasculature network from noisy and low-resolution fluorescence microscopy data that does not require the detailed segmentation of the vessel structure is proposed here. The method is most appropriate for problems where the tortuosity of the network is relatively low and proceeds by directly computing a piecewise linear approximation to the vasculature skeleton through the construction of a graph in three dimensions whose edges represent the skeletal approximation and vertices are located at Critical Points (CPs) on the microvasculature. The CPs are defined as vessel junctions or locations of relatively large curvature along the centerline of a vessel. Our method consists of two phases. First, we provide a CP detection technique that, for junctions in particular, does not require any a priori geometric information such as direction or degree. Second, connectivity between detected nodes is determined via the solution of a Binary Integer Program (BIP) whose variables determine whether a potential edge between nodes is or is not included in the final graph. The utility function in this problem reflects both intensity-based and structural information along the path connecting the two nodes. Qualitative and quantitative results confirm the usefulness and accuracy of this method. This approach provides a mean of correctly capturing the connectivity patterns in vessels that are missed by more traditional segmentation and binarization schemes because of imperfections in the images which manifest as dim or broken vessels.
本文提出了一种新方法，用于从噪声大且分辨率低的荧光显微镜数据中确定微血管网络的全局拓扑结构，该方法无需对血管结构进行详细分割。该方法最适用于网络曲折度相对较低的问题，其过程是通过在三维空间中构建一个图来直接计算血管骨架的分段线性近似，该图的边代表骨架近似，顶点位于微血管上的临界点（CPs）。CPs被定义为血管交汇处或沿血管中心线曲率相对较大的位置。我们的方法包括两个阶段。首先，我们提供一种CP检测技术，特别是对于交汇处，该技术不需要任何先验几何信息，如方向或度数。其次，通过求解一个二元整数规划（BIP）来确定检测到的节点之间的连通性，该规划的变量决定节点之间的潜在边是否包含在最终图中。该问题中的效用函数反映了沿连接两个节点的路径的基于强度的信息和结构信息。定性和定量结果证实了该方法的实用性和准确性。这种方法提供了一种手段，可以正确捕捉由于图像中的缺陷（表现为暗淡或断裂的血管）而被更传统的分割和二值化方案遗漏的血管连通模式。
