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Proceedings Paper

Evaluation of search strategies and cost functions in optimizing voxel-based image registration
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Paper Abstract

A number of image registration algorithms are currently used to register both intra-modality and inter-modality image data sets. These algorithms, although tested, have not always been optimized or evaluated in relationship to other registration algorithms available. Analysis of registration algorithms is often difficult, due to the fact that the registration components are integrated with each other and cannot be easily isolated form the rest of the algorithm. This study outlines some important features of registration algorithms and describes a method by which these algorithms may be analyzed. This method was used to analyze (1) two cost functions, a normalized standard deviation function and a conditional entropy function, (2) two search strategies, Powell's method and a derivative method, and (3) a number of iterative relaxation/data reduction techniques. These registration components were tested with a number of intra- modal and inter-modal data sets. The cost function analyses suggest that segmentation is necessary for some inter-modal registration problems. Multi-resolution techniques are also discussed with regard to registration effectiveness. A Euclidean distance measure was used to conditional entropy combined with a derivative search strategy may be the most robust approach to image registration, whereas the normalized standard deviation with Powell's search strategy produces the worst results. Generalization and further work are indicate in the discussion.

Paper Details

Date Published: 7 May 1997
PDF: 9 pages
Proc. SPIE 3031, Medical Imaging 1997: Image Display, (7 May 1997); doi: 10.1117/12.273935
Show Author Affiliations
David Richard Holmes III, Mayo Clinic and Foundation (United States)
Jon J. Camp, Mayo Clinic and Foundation (United States)
Richard A. Robb, Mayo Clinic and Foundation (United States)


Published in SPIE Proceedings Vol. 3031:
Medical Imaging 1997: Image Display
Yongmin Kim, Editor(s)

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