Computational diffusion MRI : MICCAI Workshop, Athens, Greece, October 2016 / Andrea Fuster ... [et al.] editors |
Pubbl/distr/stampa | Cham, : Springer, 2017 |
Descrizione fisica | xi, 212 p. : ill. ; 24 cm |
Soggetto topico |
92Bxx - Mathematical biology in general [MSC 2020]
65Zxx - Applications to the sciences [MSC 2020] 65Dxx - Numerical approximation and computational geometry (primarily algorithms) [MSC 2020] 62P10 - Applications of statistics to biology and medical sciences; meta analysis [MSC 2020] 65Cxx - Probabilistic methods, stochastic differential equations [MSC 2020] 00A66 - Mathematics and visual arts [MSC 2020] |
Soggetto non controllato |
Brain network analysis
Connectomics Diffusion tensor imaging Fiber tractography Image processing Inverse Problems Magnetic resonance imaging Medical image analysis Neuroimaging Segmentation |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Titolo uniforme | |
Record Nr. | UNICAMPANIA-VAN0123900 |
Cham, : Springer, 2017 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Vanvitelli | ||
|
Computational diffusion MRI : MICCAI Workshop, Munich, Germany, october 9., 2015 / Andrea Fuster ... [et al.] editors |
Pubbl/distr/stampa | [Cham], : Springer, 2016 |
Descrizione fisica | IX, 234 p. : ill. ; 24 cm |
Soggetto topico |
92Bxx - Mathematical biology in general [MSC 2020]
65Zxx - Applications to the sciences [MSC 2020] 65Dxx - Numerical approximation and computational geometry (primarily algorithms) [MSC 2020] 62P10 - Applications of statistics to biology and medical sciences; meta analysis [MSC 2020] 65Cxx - Probabilistic methods, stochastic differential equations [MSC 2020] 00A66 - Mathematics and visual arts [MSC 2020] |
Soggetto non controllato |
Brain network analysis
Connectomics Diffusion tensor imaging Fiber tractography Image processing Inverse Problems Magnetic resonance imaging Medical image analysis Neuroimaging Segmentation |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Titolo uniforme | |
Record Nr. | UNICAMPANIA-VAN0114544 |
[Cham], : Springer, 2016 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Vanvitelli | ||
|
Handbook of Variational Methods for Nonlinear Geometric Data / Philipp Grohs, Martin Holler, Andreas Weinmann editors |
Pubbl/distr/stampa | Cham, : Springer, 2020 |
Descrizione fisica | xxvi, 701 p. : ill. ; 24 cm |
Soggetto topico |
65-XX - Numerical analysis [MSC 2020]
65Mxx - Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems [MSC 2020] 65Nxx - Numerical methods for partial differential equations, boundary value problems [MSC 2020] 65Dxx - Numerical approximation and computational geometry (primarily algorithms) [MSC 2020] 00B15 - Collections of articles of miscellaneous specific interest [MSC 2020] |
Soggetto non controllato |
Applied differential geometry
Curvature regularization Denoising Diffusion tensor imaging Functional lifting techniques Geometric finite elements Geometric nonlinear data Geometry processing Labeling Manifold valued data Medical Imaging Metamorphosis models Optical flow Optimization in manifolds Statistics in manifolds Total variation Variational methods |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Titolo uniforme | |
Record Nr. | UNICAMPANIA-VAN0249334 |
Cham, : Springer, 2020 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Vanvitelli | ||
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