Wong Wilbur C K, Chung Albert C S
Lo Kwee-Seong Medical Image Analysis Laboratory, Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong.
Med Image Anal. 2007 Dec;11(6):567-87. doi: 10.1016/j.media.2007.05.003. Epub 2007 Jun 2.
We propose a novel framework to segment vessels on their cross-sections. It starts with a probabilistic vessel axis tracing in a gray-scale three-dimensional angiogram, followed by vessel boundary delineation on cross-sections derived from the extracted axis. It promotes a more intuitive delineation of vessel boundaries which are mostly round on the cross-sections. The prior probability density function of the axis tracer's formulation permits seamless integration of user guidance to produce continuous traces through regions that contain furcations, diseased portions, kissing vessels (vessels in close proximity to each other) and thin vessels. The contour that outlines the vessel boundary in a 3-D space is determined as the minimum cost path on a weighted directed acyclic graph derived from each cross-section. The user can place anchor points to force the contour to pass through. The contours obtained are tiled to approximate the vessel boundary surface. Since we use stream surfaces generated w.r.t. the traced axis as cross-sections, non-intersecting adjacent cross-sections are guaranteed. Therefore, the tiling can be achieved by joining vertices of adjacent contours. The vessel boundary surface is then deformed under constrained movements on the cross-sections and is voxelized to produce the final vascular segmentation. Experimental results on synthetic and clinical data have shown that the vessel axes extracted by our tracer are continuous and less jittered as compared with the other two trace-based algorithms. Furthermore, the segmentation algorithm with cross-sections are robust to noise and can delineate vessel boundaries that have level of variability similar to those obtained manually.
我们提出了一种用于在血管横截面进行分割的新型框架。它始于在灰度三维血管造影图中进行概率性血管轴线追踪,随后在从提取的轴线导出的横截面上进行血管边界描绘。它促进了对血管边界更直观的描绘,这些边界在横截面上大多是圆形的。轴线追踪器公式的先验概率密度函数允许无缝集成用户引导,以在包含分叉、病变部分、相邻血管(彼此靠近的血管)和细血管的区域产生连续的轨迹。在三维空间中勾勒血管边界的轮廓被确定为从每个横截面导出的加权有向无环图上的最小成本路径。用户可以放置锚点以迫使轮廓通过。获得的轮廓被平铺以近似血管边界表面。由于我们使用相对于追踪轴线生成的流面作为横截面,因此保证了相邻横截面不相交。因此,平铺可以通过连接相邻轮廓的顶点来实现。然后,血管边界表面在横截面上的约束运动下变形并体素化以产生最终的血管分割。在合成数据和临床数据上的实验结果表明,与其他两种基于追踪的算法相比,我们的追踪器提取的血管轴线是连续的且抖动较小。此外,具有横截面的分割算法对噪声具有鲁棒性,并且可以描绘出具有与手动获得的类似变化程度的血管边界。