| Effective incorporation of spatial information in a mutual information based 3D-2D registration of a CT volume to X-ray images. | |
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MedLine Citation:
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PMID: 18982693 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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This paper addresses the problem of estimating the 3D rigid pose of a CT volume of an object from its 2D X-ray projections. We use maximization of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. However, it is known that the standard mutual information measure only takes intensity values into account without considering spatial information and its robustness is questionable. In this paper, instead of directly maximizing mutual information, we propose to use a variational approximation derived from the Kullback-Leibler bound. Spatial information is then incorporated into this variational approximation using a Markov random field model. The newly derived similarity measure has a least-squares form and can be effectively minimized by a multi-resolution Levenberg-Marquardt optimizer. Experimental results are presented on X-ray and CT datasets of a plastic phantom and a cadaveric spine segment. |
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Authors:
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Guoyan Zheng |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Volume: 11 ISSN: - ISO Abbreviation: Med Image Comput Comput Assist Interv Publication Date: 2008 |
Date Detail:
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Created Date: 2008-11-05 Completed Date: 2008-12-30 Revised Date: 2012-02-23 |
Medline Journal Info:
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Nlm Unique ID: 101249582 Medline TA: Med Image Comput Comput Assist Interv Country: Germany |
Other Details:
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Languages: eng Pagination: 922-9 Citation Subset: IM |
Affiliation:
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MEM Research Center, University of Bern, Stauffacherstr. 78, CH-3014, Switzerland. guoyan.zheng@ieee.org |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms* Artificial Intelligence Imaging, Three-Dimensional / methods* Pattern Recognition, Automated / methods* Radiographic Image Enhancement / methods Radiographic Image Interpretation, Computer-Assisted / methods* Reproducibility of Results Sensitivity and Specificity Spine / radiography* Subtraction Technique* Tomography, X-Ray Computed / methods* |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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