東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Modeling, analysis, and visualizatio...

Schultz, Thomas.

Linked to FindBook

Google Book

Amazon

博客來

Modeling, analysis, and visualization of anisotropy

Record Type:	Electronic resources : Monograph/item
Title/Author:	Modeling, analysis, and visualization of anisotropy/ edited by Thomas Schultz, Evren Ozarslan, Ingrid Hotz.
other author:	Schultz, Thomas.
Published:	Cham :Springer International Publishing : : 2017.,
Description:	x, 407 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer eBooks
Subject:	Anisotropy. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-61358-1
ISBN:	9783319613581

Modeling, analysis, and visualization of anisotropy
Modeling, analysis, and visualization of anisotropy[electronic resource] /edited by Thomas Schultz, Evren Ozarslan, Ingrid Hotz. - Cham :Springer International Publishing :2017. - x, 407 p. :ill., digital ;24 cm. - Mathematics and visualization,1612-3786. - Mathematics and visualization..

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.

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.

ISBN: 9783319613581

Standard No.: 10.1007/978-3-319-61358-1doiSubjects--Topical Terms:

596747
Anisotropy.

LC Class. No.: QD941 / .M63 2017

Dewey Class. No.: 548.8

Modeling, analysis, and visualization of anisotropy
LDR:02572nmm a2200325 a 4500 001 2111043
003 DE-He213
005 20180426155531.0
006 m d
007 cr nn 008maaau
008 180619s2017 gw s 0 eng d
020 $a 9783319613581 $q (electronic bk.)
020 $a 9783319613574 $q (paper)
024 7 $a 10.1007/978-3-319-61358-1 $2 doi
035 $a 978-3-319-61358-1
040 $a GP $c GP
041 0 $a eng
050 4 $a QD941 $b .M63 2017
072 7 $a PBF $2 bicssc
072 7 $a MAT002050 $2 bisacsh
082 0 4 $a 548.8 $2 23
090 $a QD941 $b .M689 2017
245 0 0 $a Modeling, analysis, and visualization of anisotropy $h [electronic resource] / $c edited by Thomas Schultz, Evren Ozarslan, Ingrid Hotz.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2017.
300 $a x, 407 p. : $b ill., digital ; $c 24 cm.
490 1 $a Mathematics and visualization, $x 1612-3786
505 0 $a 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.
520 $a 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.
650 0 $a Anisotropy. $3 596747
650 0 $a Anisotropy $x Mathematical models. $3 713518
650 1 4 $a Mathematics. $3 515831
650 2 4 $a Linear and Multilinear Algebras, Matrix Theory. $3 891082
650 2 4 $a Computational Science and Engineering. $3 893018
650 2 4 $a Visualization. $3 586179
650 2 4 $a Image Processing and Computer Vision. $3 891070
700 1 $a Schultz, Thomas. $3 2058371
700 1 $a Ozarslan, Evren. $3 3264755
700 1 $a Hotz, Ingrid. $3 2157925
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Mathematics and visualization. $3 1568010
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-61358-1
950 $a Mathematics and Statistics (Springer-11649)