Image registration of medical images

Image registration is a vital problem in medical imaging. It has many potential applications in clinical diagnosis (e.g. diagnosis of cardiac, retinal, pelvic, renal, abdomen, liver and tissue disorders). In this paper a new technique has been proposed based on feature based image registration using SURF (Speeded up robust features) and Hessian matrix feature extraction techniques for detecting, extracting and matching corresponding points in the reference (fixed) and source image (deformed). The source image is aligned using SURF and Hessian feature extraction techniques to align with the reference image. The proposed technique is based on multimodality of images, feature based classification and non-rigid images as the images taken are from different sources like MRI, CT scan and X-ray. The proposed technique uses feature-based methods to find correspondence between image features such as points, lines and contours. The non-rigid images use fixed (source) image and also deformable (target) image of the subject and aligns target image according to source/reference image.