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- W1578832007 abstract "Mutual Information is perhaps the most widely used multimodality image registration method. A crucial step in mutual information is the estimation of the probability density function (pdf). In most cases, the Parzen window estimator is employed for this purpose which results in an excessive computational cost. In this paper we demonstrate that replacing the Parzen density estimator with a Support Vector Machine (SVM) density estimation will result in a significant reduction of the computational time. We verified this by registering 2D portal images to DRRs (digitally reconstructed radiographs) projected from 3D CT volumetric data.KeywordsSupport VectorMutual InformationSupport Vector Method MethodPortal ImageImage Registration MethodThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
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- W1578832007 date "2003-01-01" @default.
- W1578832007 modified "2023-10-16" @default.
- W1578832007 title "Support Vector Machine Density Estimator as a Generalized Parzen Windows Estimator for Mutual Information based Image Registration" @default.
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- W1578832007 doi "https://doi.org/10.1007/978-3-540-39903-2_104" @default.
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