551 Copyright © 2016, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 18 DOI: 10.4018/978-1-4666-9474-3.ch018 ABSTRACT Registration of medical images like CT-MR, MR-MR etc. are challenging area for researchers. This chap- ter introduces a new cluster based registration technique with help of the supervised optimized neural network. Features are extracted from diferent cluster of an image obtained from clustering algorithms. To overcome the drawback regarding convergence rate of neural network, an optimized neural network is proposed in this chapter. The weights are optimized to increase the convergence rate as well as to avoid stuck in local minima. Diferent clustering algorithms are explored to minimize the clustering er- ror of an image and extract features from suitable one. The supervised learning method applied to train the neural network. During this training process an optimization algorithm named Genetic Algorithm (GA) is used to update the weights of a neural network. To demonstrate the efectiveness of the proposed method, investigation is carried out on MR T1, T2 data sets. The proposed method shows convincing results in comparison with other existing techniques. INTRODUCTION Image registration or alignment and matching of two or more images, establishes a one-to-one spatial correspondence of a single 2-D/3-D scene or several similar scenes captured at different time instants or from various viewpoints or by different sensors. In image processing this is one of the important steps Cluster Based Medical Image Registration Using Optimized Neural Network Joydev Hazra Heritage Institute of Technology, India Aditi Roy Chowdhury B.P.C. Institute of Technology, India Paramartha Dutta Visva-Bharati University, India