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Optimization of a similarity metric is an essential component in intensity-based medical image registration. In this paper, an improved variable neighborhood selection based particle swarm optimization (VNS-PSO) is proposed. The PSO algorithm is co-operative, population-based global search swarm intelligence mataheuristics. The improved version of PSO algorithm possesses better ability to escape from...
Registration for sequential images has significant meanings in clinical diagnosis and analysis. Many researches are concentrated on using higher-order mutual information (HMI) to fulfill the registration task. But HMI has some disadvantages, which limit the applications of HMI to a large degree. The paper proposes a new registration measure, called nonlinear correlation information entropy (NCIE),...
In order to eliminate displacement and elastic deformation between images of adjacent frames in course of 3D ultrasonic image reconstruction, elastic registration based on morphology skeleton was adopted in this paper. Feature points of connected skeleton are extracted automatically by accounting topical curvature extreme points several times. Initial registration is processed according to barycenter...
A global optimization technique for image registration using the concept of nonlinear correlation information entropy (NCIE) as the matching criterion is presented. The method makes it possible to efficiently overcome the local minima problem utilizing the extremum property of NCIE. Furthermore, the improved downhill simplex algorithm incorporated variant accuracy tolerance can reduce the evaluation...
In this paper a new approach to the problem of rigid body registration is proposed, using a concept of nonlinear correlation information entropy (NCIE) as the new matching criterion. The presented method applies NCIE to measure the correlation degree between the image intensities of corresponding voxel in both images. Registration is achieved by adjustment of the relative position until the NCIE between...
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