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Optimization of Image Registration for Medical Image Analysis

Image registration has vital applications in medical image analysis. It is a fundamental preprocessing step where two or more images are aligned into a common coordinate system. Out of various types of registration methods, a popular category is the one, which uses the whole image content to derive a suitable transformation for overlaying the input images. Image registration itself is composed of a number of phases like transformation, interpolation, computing similarity metric and optimization of the transformation parameters (translation, rotation, shearing etc). A major factor that determines the success and effectiveness of any registration method is the optimization strategy we employ for achieving the optimal set of transformation vectors. Hence, it can be viewed as an optimization problem, which computes the geometric as well as intensity transformations at which the input images are having maximal similarity with one another. In this paper, we present a mono modal image registration algorithm for the alignment of T1-weighted MR images of human brain using modified Particle Swarm Optimization (PSO) method for getting the optimum spatial coordinates of the moving image. The experimental results clearly show that the proposed algorithm guarantees better results than the traditional PSO algorithm.