Using Voxel Similarity as a Measure of Medical Image Registration
Colin Studholme, David Hill, D.J. Hawkes · 1994
In this paper we present our work on using intensity feature spaces to study the relationship between voxel values in registered and unreg-istered medical images. By taking a simple image model we predict structures that we might expect to find in an intensity feature space produced from different modality images of the same scene. We show how this structure will be modified by image noise, misregistration and differing point spread functions of the two modalities. We show examples of such structure in feature spaces created from clinically ac-quired Magnetic Resonance (MR) and Positron Emission Tomography (PET) image data. We show how two simple measures of voxel sim-ilarity based on these feature space observations, a modified variance of intensity ratio and the 3rd order moment of the feature space his-togram, can be used to quantify image misregistration. The 3rd order moment measure is then used with a genetic optimisation algorithm to automatically register pre and post Gadolinium injection MR images. 1