Riemannian Geometric Statistics in Medical Image Analysis

Par : Xavier Pennec, Stefan Sommer, Tom Fletcher
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  • Nombre de pages614
  • PrésentationBroché
  • FormatGrand Format
  • Poids1.3 kg
  • Dimensions19,2 cm × 23,5 cm × 3,0 cm
  • ISBN978-0-12-814725-2
  • EAN9780128147252
  • Date de parution04/09/2019
  • ÉditeurAcademic press

Résumé

Over the past 15 years, there has beeria growing need in the medical image computing community for principled methods to process nonlinear geometric data. Riemannian geometry has emerged as one of the most powerful mathematical and computational frameworks for analyzing such data. Riemannian Geometric Statistics in Medical Image Analysis is a complete reference on statistics on Riemannian manifolds and more general nonlinear spaces with applications in medical image analysis.
Ir provides an introduction to the core methodology followed by a presentation of state-of-the-art methods.
Over the past 15 years, there has beeria growing need in the medical image computing community for principled methods to process nonlinear geometric data. Riemannian geometry has emerged as one of the most powerful mathematical and computational frameworks for analyzing such data. Riemannian Geometric Statistics in Medical Image Analysis is a complete reference on statistics on Riemannian manifolds and more general nonlinear spaces with applications in medical image analysis.
Ir provides an introduction to the core methodology followed by a presentation of state-of-the-art methods.