Medical image registration by combining global and local information: a chain-type diffeomorphic demons algorithm

2013 ◽  
Vol 58 (23) ◽  
pp. 8359-8378 ◽  
Author(s):  
Xiaozheng Liu ◽  
Zhenming Yuan ◽  
Junming Zhu ◽  
Dongrong Xu
Keyword(s):  
Image Registration ◽  
Medical Image ◽  
Local Information ◽  
Medical Image Registration ◽  
Demons Algorithm ◽  
A Chain ◽  
Global And Local ◽  
Chain Type

Three-dimensional lung medical image registration based on improved demons algorithm

Optik ◽  
2016 ◽  
Vol 127 (4) ◽  
pp. 1893-1899 ◽  
Author(s):  
Xiaoqi Lu ◽  
Hefeng Yu ◽  
Ying Zhao ◽  
He Hou ◽  
Yinhui Li
Keyword(s):  
Image Registration ◽  
Medical Image ◽  
Three Dimensional ◽  
Medical Image Registration ◽  
Demons Algorithm

Computing the Medical Image Registration Using Meta-Heuristics

2014 ◽  
Vol 643 ◽  
pp. 237-242 ◽  
Author(s):  
Tahari Abdou El Karim ◽  
Bendakmousse Abdeslam ◽  
Ait Aoudia Samy
Keyword(s):  
Image Processing ◽  
Genetic Algorithms ◽  
Simulated Annealing ◽  
Image Registration ◽  
Cost Function ◽  
Population Genetic ◽  
Medical Image ◽  
Medical Image Registration ◽  
Anatomical Structures

The image registration is a very important task in image processing. In the field of medical imaging, it is used to compare the anatomical structures of two or more images taken at different time to track for example the evolution of a disease. Intensity-based techniques are widely used in the multi-modal registration. To have the best registration, a cost function expressing the similarity between these images is maximized. The registration problem is reduced to the optimization of a cost function. We propose to use neighborhood meta-heuristics (tabu search, simulated annealing) and a meta-heuristic population (genetic algorithms). An evaluation step is necessary to estimate the quality of registration obtained. In this paper we present some results of medical image registration

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