Multi-grid transformation for medical image registration

Abstract

It is an enormous challenge to register different physical brain images to each other, or to register a set of brain images from different modalities such as CT, MRI, SPECT, and PET. Image registration is the process of aligning the different sets of data of the same object into a common coordinate system thus aligning them in order to analyze subtle changes among each other. This study proposes a new approach of registration for brain images based on Multi-Grid Transformation. The novelty of the method is that the correlation of functional brain image data obtained from different individuals can be achieved by registration of the corresponding anatomical brain images using the smart transition of grid. The Bilinear and Affine Transformations have been used in order to maintain geometric alignment throughout the process. The major benefit of the study involves integrating the images to create a composite view, extracting information that would be impossible to obtain from a single image. Therefore, the doctor can observe the variety of brain scanned images to do the diagnosis and therapy planning for clinical analysis at the same time.