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Statistical Analysis of Diffusion Tensor Imaging - Diwei Zhou
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Diwei Zhou:
Statistical Analysis of Diffusion Tensor Imaging - nuovo libro

2011, ISBN: 9783847307877

ID: 862597753

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. Statistical Methodologies for Medical Image Analysis Buch (fremdspr.) Taschenbuch 01.12.2011 Bücher>Fremdsprachige Bücher>Englische Bücher, LAP LAMBERT Academic Publishing, .201

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Statistical Analysis of Diffusion Tensor Imaging - Diwei Zhou
libro esaurito
(*)
Diwei Zhou:
Statistical Analysis of Diffusion Tensor Imaging - nuovo libro

ISBN: 9783847307877

ID: 1087396868

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. Statistical Methodologies for Medical Image Analysis Buch (fremdspr.) Bücher>Fremdsprachige Bücher>Englische Bücher, LAP LAMBERT Academic Publishing

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Statistical Analysis of Diffusion Tensor Imaging - Diwei Zhou
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Diwei Zhou:
Statistical Analysis of Diffusion Tensor Imaging - edizione con copertina flessibile

ISBN: 9783847307877

Paperback, [PU: LAP Lambert Academic Publishing], 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., Mathematics

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(*) Libro esaurito significa che il libro non è attualmente disponibile in una qualsiasi delle piattaforme associate che di ricerca.
Statistical Analysis of Diffusion Tensor Imaging
libro esaurito
(*)
Statistical Analysis of Diffusion Tensor Imaging - nuovo libro

ISBN: 9783847307877

ID: 855791a4ade456a866c7afe6f57c5a77

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. Bücher / Naturwissenschaften, Medizin, Informatik & Technik / Mathematik

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Statistical Analysis of Diffusion Tensor Imaging
libro esaurito
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Statistical Analysis of Diffusion Tensor Imaging - nuovo libro

ISBN: 3847307878

ID: 18126644

Statistical Analysis of Diffusion Tensor Imaging ab 68 EURO Statistical Methodologies for Medical Image Analysis Medien > Bücher

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Informazioni dettagliate del libro - Statistical Analysis of Diffusion Tensor Imaging


EAN (ISBN-13): 9783847307877
ISBN (ISBN-10): 3847307878
Copertina rigida
Copertina flessibile
Anno di pubblicazione: 2011
Editore: AV Akademikerverlag GmbH & Co. KG.

Libro nella banca dati dal 15.06.2007 02:46:10
libro trovato per l'ultima volta il13.02.2019 19:29:55
ISBN/EAN: 9783847307877

ISBN - Stili di scrittura alternativi:
3-8473-0787-8, 978-3-8473-0787-7


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