Improved tensor scale computation with application to medical image interpolation.
Improved tensor scale computation with application to medical image interpolation.
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DOI：
10.1016/j.compmedimag.2010.09.007
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发表时间：
2011-01
影响因子：
5.7
通讯作者：
Saha, Punam K.
中科院分区：
文献类型：
--
作者：
Xu, Ziyue;Sonka, Milan;Saha, Punam K.
张量尺度（t-scale）是局部结构形态的参数化表示，同时描述其方向、形状和各向同性尺度。在任何图像位置，t尺度表示以该位置为中心并包含在同一均匀区域中的最大椭圆（三维椭圆体）。在这里，我们提出了一种改进的算法的t尺度计算，并研究其应用于图像插值。具体地说，改进了t尺度计算算法：（1）提高了识别局部结构边界的精度;（2）在椭圆拟合中结合了代数和几何方法。在插值的上下文中，一个封闭的形式的解决方案，以确定插值线在每个图像位置的灰度图像使用相邻切片的t尺度信息。在图像切片上的每个位置处，该方法从其t尺度导出法向量，该法向量产生局部结构的跨方向并且指向最近的边缘点。在两个相邻切片上的匹配二维位置处的法向量用于使用闭合形式方程来计算插值线。该方法已被应用到BrainWeb数据集和其他几个图像从临床应用和它的准确性和响应噪声和其他图像退化的因素进行了检查，并与目前最先进的插值方法。实验结果表明，与现有的插值算法相比，新的基于t尺度的插值方法具有优越性。此外，定量分析的基础上的配对t检验的残留误差已经确定，使用t尺度为基础的插值观察到的改善是统计上显着的。
Tensor scale (t-scale) is a parametric representation of local structure morphology that simultaneously describes its orientation, shape and isotropic scale. At any image location, t-scale represents the largest ellipse (an ellipsoid in three dimensions) centered at that location and contained in the same homogeneous region. Here, we present an improved algorithm for t-scale computation and study its application to image interpolation. Specifically, the t-scale computation algorithm is improved by: (1) enhancing the accuracy of identifying local structure boundary and (2) combining both algebraic and geometric approaches in ellipse fitting. In the context of interpolation, a closed form solution is presented to determine the interpolation line at each image location in a gray level image using t-scale information of adjacent slices. At each location on an image slice, the method derives normal vector from its t-scale that yields trans-orientation of the local structure and points to the closest edge point. Normal vectors at the matching two-dimensional locations on two adjacent slices are used to compute the interpolation line using a closed form equation. The method has been applied to BrainWeb data sets and to several other images from clinical applications and its accuracy and response to noise and other image-degrading factors have been examined and compared with those of current state-of-the-art interpolation methods. Experimental results have established the superiority of the new t-scale based interpolation method as compared to existing interpolation algorithms. Also, a quantitative analysis based on the paired t-test of residual errors has ascertained that the improvements observed using the t-scale based interpolation are statistically significant.
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影响因子：
4.5
作者：
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通讯作者：
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1999-05-01
影响因子：
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作者：
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