Registration of Multimodality Medical Imaging of Brain using Particle Swarm Optimization Mahua Bhattacharya 1,* and Arpita Das 2 1 Indian Institute of Information Technology & Management, Gwalior Morena Link Road, Gwalior-474003, India * Corresponding author e-mail: mb@iiitm.ac.in 2 Institute of Radio Physics & Electronics, University of Calcutta 92, A.P.C. Road, Kolkata-700009 2 e-mail: dasarpita_rpe@yahoo.co.in Abstract: In present work we have introduced nonlinear affine registration method to incorporate the anatomic body deformation. The present technique has been developed for registration of section of human brain using CT and MR modalities. Present study related to image registration of different modality imaging is based on 2-D/2-D affine registration technique. Automatic registration has been achieved by maximization of a similarity measure and which is the correlation function of two images. The proposed method has been implemented by choosing a realistic, practical transformation and optimization techniques. Since similarity metric is a non-convex function and contains many local optima, choice of search strategy for optimization is important in registration problem. There exist many optimization schemes, most of which are local and require a starting point. Presently, we have implemented multiresolution based particle swarm optimization technique to overcome this problem. 1 Introduction Medical imaging provides insights into the size, shape and spatial relationships among anatomical structures. In radiotherapy planning, dose calculation is based on the computed tomography (CT) data, while tumor outlining is often better performed in the corresponding magnetic resonance imaging (MRI). These images are used in a complimentary manner to gain additional insights into the phenomenon. The different modalities must be appropriately combined or fused to extract more useful information for diagnosis from the fused data [2, 16]. Before images can be fused, they must be geometrically aligned. This alignment process is known as registration [1, 2]. We have already done experiment on