DocumentCode :
631765
Title :
Genetic algorithms for Voxel-based medical image registration
Author :
Valsecchi, Andrea ; Damas, Sergio ; Santamaria, J. ; Marrakchi-Kacem, Linda
Author_Institution :
Eur. Centre for Soft Comput., Mieres, Spain
fYear :
2013
fDate :
16-19 April 2013
Firstpage :
22
Lastpage :
29
Abstract :
Image registration (IR) - the task of aligning different images having a common content - is a fundamental problem in computer vision. In particular, IR is one of the key steps in medical imaging, with applications ranging from computer assisted diagnosis to computer aided therapy and surgery. As IR can be formulated as an optimization problem, a large family of metaheuristics methods can be used to improve the results obtained by classic gradient-based, continuous optimization techniques. In this work, we extend our previous intensity-based image registration (IR) technique based on a real-coded genetic algorithm with a more appropriate design. The performance evaluation of an heterogeneous group of state-of-the-art IR techniques is also extended to two experimental studies on both synthetic and real-word medical IR problems. The results prove the accuracy and applicability of our new method.
Keywords :
biomedical MRI; brain; computer vision; genetic algorithms; image registration; medical image processing; computer aided surgery; computer aided therapy; computer assisted diagnosis; computer vision; continuous optimization technique; genetic algorithm; gradient-based technique; image alignment; intensity-based image registration technique; metaheuristics method; voxel-based medical image registration; Algorithm design and analysis; Biomedical imaging; Genetic algorithms; Image resolution; Magnetic resonance imaging; Measurement; Optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence in Medical Imaging (CIMI), 2013 IEEE Fourth International Workshop on
Conference_Location :
Singapore
ISSN :
2326-991X
Print_ISBN :
978-1-4673-5919-1
Type :
conf
DOI :
10.1109/CIMI.2013.6583853
Filename :
6583853
Link To Document :
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