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The journal receives submitted manuscripts via email only. Please submit your research paper in .doc or.pdf format to the submission email: ijpmbs@ejournal.net.
You’ll be given a paper number if your submission is successful. Your paper then will undergo peer review process, which may take approximately one and a half months under normal circumstances, three tops.
After blind peer review, you will receive the notification letter with the review result of your paper...
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The journal publishes full research papers.[Read More]
 

Medical Image Registration Based on an Improved Ant Colony Optimization Algorithm

Ting Xun Lin and Herng Hua Chang
Computational Biomedical Engineering Laboratory (CBEL), Department of Engineering Science and Ocean Engineering, National Taiwan University, Daan 10617 Taipei, Taiwan

Abstract—Image registration is one of the fundamental and essential tasks within image processing. It is the process of determining the correspondence between structures in two images, which are called the template image and the reference image, respectively. The challenge of registration is to find an optimal geometric transformation between corresponding image data. This paper develops a new image registration algorithm that is based on an improved ant colony optimization algorithm. In our approach, the image pixels are treated as the nest of a swarm of ants. The ants are designed to have the ability to forage for the “food” in their memory. Subsequently, the ants deposit pheromone on the pixels, which affect the motion of the ants. The registration process of updating the pheromone, the direction and distance of advancement is repeated until the correlation coefficient between the registered and reference images reaches a maximum. Experimental results indicate that our method accurately transformed the template images into reference images in various scenarios. It is indicated that the proposed method is of potential in a wide variety of image registration applications.

Index Terms—ant colony algorithm, image registration, transition probability

Cite: Ting Xun Lin and Herng Hua Chang, "Medical Image Registration Based on an Improved Ant Colony Optimization Algorithm," International Journal of Pharma Medicine and Biological Sciences, Vol. 5, No. 1, pp. 17-22, January 2016. doi: 10.18178/ijpmbs.5.1.17-22
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