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Study on Human Brain Registration Process Using Mutual Information and Evolutionary Algorithms

  • Mahua Bhattacharya
  • Arpita Das
Chapter

Abstract

The registration of brain images is required to facilitate the study of brain mapping, treatment planning, and image-guided therapies of nervous system. In the present work a similarity measure has been implemented for affine multimodality (MR and CT) image registration of sections of the human brain. In addition, a similarity measure is built on both intensity and gradient-based images. In the present work, the region of interest (ROI), the ventricular region, is segmented using the fuzzy c-means clustering technique. The deformation or change of shape of the ventricular region captures the process of degeneracy and other abnormality in tissue regions of the human brain. The similarity metric should be maximal when two images are perfectly aligned. The genetic algorithm-based search strategy has been utilized to optimize the registration process.

Keywords

Genetic Algorithm Mutual Information Cluster Center Reference Image Image Registration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors would like to thank Dr. S. K. Sharma, Director, EKO Imaging and X-Ray Institute, Kolkata and All India Institute of Medical Sciences, New Delhi.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Information Communication TechnologyABV-Indian Institute of Information Technology and ManagementGwaliorIndia
  2. 2.Institute of Radio Physics and ElectronicsUniversity of CalcuttaCalcuttaIndia

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