Paper
8 March 2007 Improved elastic medical image registration using mutual information
Author Affiliations +
Abstract
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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Konstantin Ens, Hanno Schumacher, Astrid Franz, and 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
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Cited by 7 scholarly publications.
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KEYWORDS
Image registration

Distance measurement

Computed tomography

Positron emission tomography

Image processing

Medical imaging

Tumors

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