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Image of Anisotropy across fields and scales

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Anisotropy across fields and scales

Özarslan, Evren - Personal Name; Schultz, Thomas - Personal Name; Zhang, Eugene - Personal Name; Fuster, Andrea - Personal Name;

This open access book focuses on processing, modeling, and visualization of anisotropy information, which are often addressed by employing sophisticated mathematical constructs such as tensors and other higher-order descriptors. It also discusses adaptations of such constructs to problems encountered in seemingly dissimilar areas of medical imaging, physical sciences, and engineering. Featuring original research contributions as well as insightful reviews for scientists interested in handling anisotropy information, it covers topics such as pertinent geometric and algebraic properties of tensors and tensor fields, challenges faced in processing and visualizing different types of data, statistical techniques for data processing, and specific applications like mapping white-matter fiber tracts in the brain.

The book helps readers grasp the current challenges in the field and provides information on the techniques devised to address them. Further, it facilitates the transfer of knowledge between different disciplines in order to advance the research frontiers in these areas.

This multidisciplinary book presents, in part, the outcomes of the seventh in a series of Dagstuhl seminars devoted to visualization and processing of tensor fields and higher-order descriptors, which was held in Dagstuhl, Germany, on October 28–November 2, 2018.


Availability

No copy data

Detail Information
Series Title
-
Call Number
515.63 ANI a
Publisher
Cham, Switzerland : Springer Open., 2021
Collation
x, 280p. : ill.
Language
English
ISBN/ISSN
9783030562151
Classification
515.63
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Mathematics
Computer science--Mathematics
Mathematical physics
Algebra
Optical data processing
Tensor fields
Anisotropy
Visualization
Specific Detail Info
-
Statement of Responsibility
edited by Evren Özarslan et al.
Other version/related

No other version available

File Attachment
  • 9783030562151
    https://link.springer.com/book/10.1007/978-3-030-56215-1
    Other Resource Link
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