DocumentCode :
712922
Title :
Structural image representation for image registration
Author :
Aghajani, Khadijeh ; Shirpour, Mohsen ; Manzuri, M.T.
Author_Institution :
Dept. of Comput. Eng., Sharif Univ. of Technol., Tehran, Iran
fYear :
2015
fDate :
3-5 March 2015
Firstpage :
95
Lastpage :
100
Abstract :
Image registration is an important task in medical image processing. Assuming spatially stationary intensity relation among images, conventional area based algorithms such as CC (Correlation Coefficients) and MI (Mutual Information), show weaker results alongside spatially varying intensity distortion. In this research, a structural representation of images is introduced. It allows us to use simpler similarity metrics in multimodal images which are also robust against the mentioned distortion field. The efficiency of this presentation in non-rigid image registration in the presence of spatial varying distortion field is examined. Experimental results on synthetic and real-world data sets demonstrate the effectiveness of the proposed method for image registration tasks.
Keywords :
biomedical MRI; image registration; image representation; medical image processing; distortion field; image registration; medical image processing; multimodal images; nonrigid image registration; real-world data sets; similarity metrics; spatially stationary intensity relation; spatially varying intensity distortion; structural image representation; synthetic data sets; Additives; Algorithm design and analysis; Distortion; Entropy; Image registration; Mathematical model; Measurement; Image Registration; Phase Congruency; Structural Image Representation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Signal Processing (AISP), 2015 International Symposium on
Conference_Location :
Mashhad
Print_ISBN :
978-1-4799-8817-4
Type :
conf
DOI :
10.1109/AISP.2015.7123534
Filename :
7123534
Link To Document :
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