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Medical image registration is the task of bringing two images into spatial alignment. Automatic and accurate 3D co-registration of nuclear medicine 3D image data with 3D anatomical data is crucial for improving the functional image reconstruction through anatomy-based attenuation correction. Co-registration is also important for the fusion of anatomical data with functional information. Most registration methods involve optimizing an intensity-based similarity metric that is defined by the transformation parameters. Since its adoption, mutual information has become the typical similarity metric for multi-modal image registrations. In our research, we will develop techniques to co-register single photo emission computed tomography (SPECT) images with x-ray computer tomography (CT) in order to provide structural information for enhancing the reconstruction of SPECT images and also to localize functional activities in the body in relation to anatomy (eg blood perfusion in tumours, heart ventricles, kidneys) etc. Special radiopharmaceuticals may be used to highlight regions of activity.
Dr. Ghassan Hamarneh
Vancouver Coastal Health Authority
Simon Fraser University
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