Comparison Between Parzen Window Interpolation and Generalised Partial Volume Estimation for Nonrigid Image Registration Using Mutual Information
Comparison Between Parzen Window Interpolation and Generalised Partial Volume Estimation for Nonrigid Image Registration Using Mutual Information
复制标题
使用互信息的非刚性图像配准的 Parzen 窗插值与广义部分体积估计之间的比较
DOI:
10.1007/11784012_25
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发表时间:
2006
期刊:
影响因子:
--
通讯作者:
P. Suetens
中科院分区:
文献类型:
--
作者:
D. Loeckx;F. Maes;D. Vandermeulen;P. Suetens
Because of its robustness and accuracy for a variety of applications, either monomodal or multimodal, mutual information (MI) is a very popular similarity measure for (medical) image registration. Calculation of MI is based on the joint histogram of the two images to be registered, expressing the statistical relationship between image intensities at corresponding positions. However, the calculation of the joint histogram is not straightforward. The discrete nature of digital images, sampled as well in the intensity as in the spatial domain, impedes the exact calculation of the joint histogram. Moreover, during registration often an intensity will be sought at a non grid position of the floating image.This article compares the robustness and accuracy of two common histogram estimators in the context of nonrigid multiresolution medical image registration: a Parzen window intensity interpolator (IIP) and generalised partial volume histogram estimation (GPV). Starting from the BrainWeb data and realistic deformation fields obtained from patient images, the experiments show that GPV is more robust, while IIP is more accurate. Using a combined approach, an average registration error of 0.12 mm for intramodal and 0.30 mm for intermodal registration is achieved.