3D segmentation of medical images using a fast multistage hybrid algorithm
3D segmentation of medical images using a fast multistage hybrid algorithm
复制标题
使用快速多级混合算法对医学图像进行 3D 分割
DOI：
10.1007/s11548-006-0001-4
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发表时间：
2006-03-01
影响因子：
3
通讯作者：
Peters, Terry
中科院分区：
文献类型：
--
作者：
Gu, Lixu;Peters, Terry
本文提出了一种用于医学图像三维分割的快速多级混合算法。首先采用形态学递归腐蚀操作减少待分割对象与其邻域之间的连通性，然后采用快速行进方法大大加速表面前沿从用户定义的种子结构到靠近期望边界的表面的初始传播，然后在该表面上进行形态学重建以获得初始分割结果，最后利用形态学重建算法对初始分割结果进行分割。并且最后采用形态递归膨胀来恢复在算法的第一阶段中丢失的任何结构。该方法在60个脑、心脏和泌尿系统的CT或MRI图像上进行了测试，以证明该技术在各种成像模式和器官系统中的鲁棒性。该算法也验证了对数据集的“真理”是已知的。这些测量结果显示，该算法在三个器官系统中实现了0.966的平均“相似性指数”。当在运行Windows NT的550 MHz基于Dual PIII的PC上运行时，该算法的执行时间分别为38、46和23 s，并且从脑MRI提取皮质，从动态CT提取心脏表面，从3D CT提取肾脏。
In this paper, we propose a fast multistage hybrid algorithm for 3D segmentation of medical images. We first employ a morphological recursive erosion operation to reduce the connectivity between the object to be segmented and its neighborhood; then the fast marching method is used to greatly accelerate the initial propagation of a surface front from the user defined seed structure to a surface close to the desired boundary; a morphological reconstruction method then operates on this surface to achieve an initial segmentation result; and finally morphological recursive dilation is employed to recover any structure lost in the first stage of the algorithm. This approach is tested on 60 CT or MRI images of the brain, heart and urinary system, to demonstrate the robustness of this technique across a variety of imaging modalities and organ systems. The algorithm is also validated against datasets for which “truth” is known. These measurements revealed that the algorithm achieved a mean “similarity index” of 0.966 across the three organ systems. The execution time for this algorithm, when run on a 550 MHz Dual PIII-based PC runningWindows NT, and extracting the cortex from brain MRIs, the cardiac surface from dynamic CT, and the kidneys from 3D CT, was 38, 46 and 23 s, respectively.