Modeling, Analysis, and Visualization of Anisotropy

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Schultz, Thomas (Επιμελητής έκδοσης), Özarslan, Evren (Επιμελητής έκδοσης), Hotz, Ingrid (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2017.
• Σειρά: Mathematics and Visualization,
• Θέματα: Mathematics.; Image processing.; Matrix theory.; Algebra.; Computer mathematics.; Visualization.; Linear and Multilinear Algebras, Matrix Theory.; Computational Science and Engineering.; Image Processing and Computer Vision.

 This book focuses on the modeling, processing and visualization of anisotropy, irrespective of the context in which it emerges, using state-of-the-art mathematical tools. As such, it differs substantially from conventional reference works, which are centered on a particular application. It covers the following topics: (i) the geometric structure of tensors, (ii) statistical methods for tensor field processing, (iii) challenges in mapping neural connectivity and structural mechanics, (iv) processing of uncertainty, and (v) visualizing higher-order representations. In addition to original research contributions, it provides insightful reviews. This multidisciplinary book is the sixth in a series that aims to foster scientific exchange between communities employing tensors and other higher-order representations of directionally dependent data. A significant number of the chapters were co-authored by the participants of the workshop titled Multidisciplinary Approaches to Multivalued Data: Modeling, Visualization, Analysis, which was held in Dagstuhl, Germany in April 2016. It offers a valuable resource for those working in the field of multi-directional data, vital inspirations for the development of new models, and essential analysis and visualization techniques, thus furthering the state-of-the-art in studies involving anisotropy. 

 Part I: Features and Visualization -- Part II: Image Processing and Analysis -- Part III: Diffusion Modeling and Microstructure -- Part IV: Tractography -- Part V: Machine Learning Approaches.