DocumentCode :
3108028
Title :
Multimodality Image Registration Utilizing Ant Colony Algorithm
Author :
Rezaei, Hadi ; Shakeri, Majid ; Azadi, Sassan ; Jaferzade, Keyvan
Author_Institution :
Semnan Univ., Semnan, Iran
fYear :
2009
fDate :
28-30 Dec. 2009
Firstpage :
49
Lastpage :
53
Abstract :
Image registration is the determination of a geometrical transformation that aligns points in one image of an object with corresponding points in another image. To find the best transformation function we should optimize the similarity measure. The optimization methods are generally divided into two general classes of global and local methods. The problem with local methods is that they trap in local optima. So, in this paper, we use ant colony algorithm as a global optimization method which is based on real ant behavior. The results of our experiments show the effectiveness and better accuracy for this method rather than local methods.
Keywords :
image registration; optimisation; ant colony algorithm; geometrical transformation; global optimization method; multimodality image registration; similarity measure; Ant colony optimization; Biomedical imaging; Computed tomography; High-resolution imaging; Image registration; Machine vision; Magnetic resonance imaging; Optimization methods; Positron emission tomography; Ultrasonic imaging; Geometric Transformation; Multimidality Image Registration; Optimization Methods; Similarity Measure;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Vision, 2009. ICMV '09. Second International Conference on
Conference_Location :
Dubai
Print_ISBN :
978-0-7695-3944-7
Electronic_ISBN :
978-1-4244-5645-1
Type :
conf
DOI :
10.1109/ICMV.2009.21
Filename :
5381083
Link To Document :
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