Statistical analysis diffusion tensor di zhou diwei (10 risultati)
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Condizione: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.
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Taschenbuch. Condizione: Neu. Statistical Analysis of Diffusion Tensor Imaging | Statistical Methodologies for Medical Image Analysis | Diwei Zhou | Taschenbuch | 200 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783847307877 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norde…rstedt, info[at]bod[dot]de | Anbieter: preigu.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This thesis tackles three major challenges in diffusion tensor imaging analysis with statistical methodologies. We firstly develop a novel Bayesian multi-tensor model with reparameterisation for capturing water diffusion at voxels…with one or more distinct fibre orientations. A mixture Markov chain Monte Carlo (MCMC) algorithm is then developed to study the uncertainty of fibre orientations. Secondly, we apply non-Euclidean statistics to define the sample mean of diffusion tensor data which are employed for tensor field processing. In particular, Procrustes analysis, a powerful statistical shape analysis tool, is compared with the Log-Euclidean, Riemannian, Cholesky and power Euclidean approaches. A new anisotropy measure, Procrustes anisotropy, is defined. We finally use directional statistics to design uniformly distributed diffusion gradient direction schemes with different numbers of directions. All methods are illustrated through synthetic examples as well as white matter tractography of a healthy human brain. 200 pp. Englisch.
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Zhou DiweiDr. Diwei Zhou received her PhD in Statistics from University of Nottingham (2010). She worked as a Marie Curie fellow for a medical image analysis project in School of Mathematical Sciences…in University of Nottingham (200.
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This thesis tackles three major challenges in diffusion tensor imaging analysis with statistical methodologies. We firstly develop a novel Bayesian multi-tensor model with reparameterisation for capturing water diffusion at voxels with… one or more distinct fibre orientations. A mixture Markov chain Monte Carlo (MCMC) algorithm is then developed to study the uncertainty of fibre orientations. Secondly, we apply non-Euclidean statistics to define the sample mean of diffusion tensor data which are employed for tensor field processing. In particular, Procrustes analysis, a powerful statistical shape analysis tool, is compared with the Log-Euclidean, Riemannian, Cholesky and power Euclidean approaches. A new anisotropy measure, Procrustes anisotropy, is defined. We finally use directional statistics to design uniformly distributed diffusion gradient direction schemes with different numbers of directions. All methods are illustrated through synthetic examples as well as white matter tractography of a healthy human brain.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 200 pp. Englisch.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This thesis tackles three major challenges in diffusion tensor imaging analysis with statistical methodologies. We firstly develop a novel Bayesian multi-tensor model with reparameterisation for capturing water diffusion at voxels with…one or more distinct fibre orientations. A mixture Markov chain Monte Carlo (MCMC) algorithm is then developed to study the uncertainty of fibre orientations. Secondly, we apply non-Euclidean statistics to define the sample mean of diffusion tensor data which are employed for tensor field processing. In particular, Procrustes analysis, a powerful statistical shape analysis tool, is compared with the Log-Euclidean, Riemannian, Cholesky and power Euclidean approaches. A new anisotropy measure, Procrustes anisotropy, is defined. We finally use directional statistics to design uniformly distributed diffusion gradient direction schemes with different numbers of directions. All methods are illustrated through synthetic examples as well as white matter tractography of a healthy human brain.
