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8 March 2007Improved elastic medical image registration using mutual information
One of the future-oriented areas of medical image processing is to develop fast and exact algorithms for image
registration. By joining multi-modal images we are able to compensate the disadvantages of one imaging modality
with the advantages of another modality. For instance, a Computed Tomography (CT) image containing the
anatomy can be combined with metabolic information of a Positron Emission Tomography (PET) image. It is
quite conceivable that a patient will not have the same position in both imaging systems. Furthermore some
regions for instance in the abdomen can vary in shape and position due to different filling of the rectum. So a
multi-modal image registration is needed to calculate a deformation field for one image in order to maximize the
similarity between the two images, described by a so-called distance measure.
In this work, we present a method to adapt a multi-modal distance measure, here mutual information (MI),
with weighting masks. These masks are used to enhance relevant image structures and suppress image regions
which otherwise would disturb the registration process. The performance of our method is tested on phantom
data and real medical images.
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Konstantin Ens, Hanno Schumacher, Astrid Franz, Bernd Fischer, "Improved elastic medical image registration using mutual information," Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 65122C (8 March 2007); https://doi.org/10.1117/12.707632