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• W30926880 abstract "The computational anatomy project has largely been a study of large deformations via diffeomorphic mapping. This article looks at various estimation problems within this setting, including disease scoring, segmentation, and template estimation. All are posed in the augmented orbit of unions of multiple atlases or templates. These make our generative Bayesian probability models multimodal, in which the posterior probability of interpreting a single image is shared across multiple atlases. We derive the maximum a posteriori estimation in this multimodal context for (i) disease scoring/classification of a single target image given multiple disease cohorts, (ii) segmentation of images, and (iii) atlas generation from populations." @default.
• W30926880 created "2016-06-24" @default.
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• W30926880 date "2015-01-01" @default.
• W30926880 modified "2023-10-02" @default.
• W30926880 title "Bayesian Multiple Atlas Deformable Templates" @default.
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• W30926880 doi "https://doi.org/10.1016/b978-0-12-397025-1.00312-2" @default.
• W30926880 hasPublicationYear "2015" @default.
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