Wyatt Christopher L, Ge Yaorong, Vining David J
Wake Forest University School of Medicine, Medical Centre Boulevard, Winston-Salem, NC, USA.
Comput Med Imaging Graph. 2006 Jan;30(1):17-30. doi: 10.1016/j.compmedimag.2005.07.003. Epub 2006 Jan 18.
The Geometric Deformable Model is developed for accurate colon lumen segmentation as part of an automatic Virtual Colonoscopy system. The deformable model refines the lumen surface found by an automatic seed location and thresholding procedure. The challenges to applying the deformable model are described, showing the definition of the stopping function as the key to accurate segmentation. The limitations of current stopping criteria are examined and a new definition, tailored to the task of colon segmentation, is given. First, a multiscale edge operator is used to locate high confidence boundaries. These boundaries are then integrated into the stopping function using a distance transform. The hypothesis is that the new stopping function results in a more accurate representation of the lumen surface compared to previous monotonic functions of the gradient magnitude. This hypothesis is tested using observer ratings of colon surface fidelity at 100,000 randomly selected locations in each of four datasets. The results show that the surfaces determined by the modified deformable model better represent the lumen surface overall.
几何可变形模型是作为自动虚拟结肠镜检查系统的一部分而开发的，用于精确的结肠腔分割。该可变形模型对通过自动种子定位和阈值处理过程找到的腔表面进行细化。描述了应用可变形模型所面临的挑战，表明停止函数的定义是精确分割的关键。研究了当前停止标准的局限性，并给出了针对结肠分割任务量身定制的新定义。首先，使用多尺度边缘算子来定位高置信度边界。然后，利用距离变换将这些边界整合到停止函数中。假设是，与之前基于梯度幅值的单调函数相比，新的停止函数能更准确地表示腔表面。在四个数据集中的每一个中，在100,000个随机选择的位置使用结肠表面保真度的观察者评分对这一假设进行了测试。结果表明，由改进后的可变形模型确定的表面总体上能更好地表示腔表面。
