Department of Pathology, Box 1194, Mount Sinai School of Medicine, One Gustave L. Levy Place, New York, NY 10029, USA.
Comput Methods Programs Biomed. 2010 Mar;97(3):223-31. doi: 10.1016/j.cmpb.2009.07.002. Epub 2009 Jul 30.
In this paper, we present a semi-automatic algorithm for measurement of the glomerular basement membrane thickness in electron microscopy kidney images. A string of sparsely spaced points are manually inputted along the central line of the basement membrane (lamina densa) to be measured. The gaps between successive input points are lineally interpolated. A nonlinear mapping is applied to straighten the curved central line. Two distance functions of edges to the central line are constructed. The smooth envelope lines are obtained by repetitive applications of a linear low-pass filtering followed by a comparing and selecting process. The boundaries of the glomerular basement membrane are obtained from the inverse mapping of the envelope functions. The average basement membrane thickness is estimated as the ratio of the basement membrane area to the length of the central line.
本文提出了一种半自动算法，用于测量电子显微镜肾脏图像中的肾小球基底膜厚度。沿着要测量的基底膜（致密层）的中心线手动输入一串稀疏的点。连续输入点之间的间隙进行线性内插。应用非线性映射将弯曲的中心线拉直。构建了两个到中心线的边缘距离函数。通过重复应用线性低通滤波然后进行比较和选择过程来获得平滑的包络线。从包络函数的逆映射中获得肾小球基底膜的边界。基底膜的平均厚度估计为基底膜面积与中心线长度的比值。
