A viscous fluid model for multimodal non-rigid image registration using mutual information

作     者：D'Agostino, E Maes, F Vandermeulen, D Suetens, P 

作者机构：Katholieke Univ Leuven Univ Hosp Med Image Comp Radiol ESAT PSI Fac Med B-3000 Louvain Belgium Katholieke Univ Leuven Univ Hosp Med Image Comp Radiol ESAT PSI Fac Engn B-3000 Louvain Belgium 

出 版 物：《MEDICAL IMAGE ANALYSIS》 (医学图像分析)

年 卷 期：2003年第7卷第4期

页      面：565-575页

核心收录：

学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 0812[工学-计算机科学与技术（可授工学、理学学位）] 1009[医学-特种医学] 10[医学] 

主　　题：non-rigid-registration mutual information viscous fluid model 

摘      要：We propose a multimodal free-form registration algorithm based on maximization of mutual information. The warped image is modeled as a viscous fluid that deforms under the influence of forces derived from the gradient of the mutual information registration criterion. Parzen windowing is used to estimate the joint intensity probability of the images to be matched. The method is evaluated for non-rigid inter-subject registration of MR brain images. The accuracy of the method is verified using simulated multi-modal MR images with known ground truth deformation. The results show that the root mean square difference between the recovered and the ground truth deformation is smaller than 1 voxel. We illustrate the application of the method for atlas-based brain tissue segmentation in MR images in case of gross morphological differences between atlas and patient images. (C) 2003 Elsevier B.V. All rights reserved.