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  Using Eigenvalue Derivatives for Edge Detection in DT-MRI Data

Schultz, T., & Seidel, H.-P. (2008). Using Eigenvalue Derivatives for Edge Detection in DT-MRI Data. In G. Rigoll (Ed.), Pattern Recognition: 30th DAGM Symposium (pp. 193-202). Berlin: Springer.

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 Creators:
Schultz, Thomas1, Author           
Seidel, Hans-Peter1, Author           
Affiliations:
1Computer Graphics, MPI for Informatics, Max Planck Society, ou_40047              

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 Abstract: This paper introduces eigenvalue derivatives as a fundamental tool to discern the different types of edges present in matrix-valued images. It reviews basic results from perturbation theory, which allow one to compute such derivatives, and shows how they can be used to obtain novel edge detectors for matrix-valued images. It is demonstrated that previous methods for edge detection in matrix-valued images are simplified by considering them in terms of eigenvalue derivatives. Moreover, eigenvalue derivatives are used to analyze and refine the recently proposed Log-Euclidean edge detector. Application examples focus on data from diffusion tensor magnetic resonance imaging (DT-MRI).

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Language(s): eng - English
 Dates: 2009-03-192008
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 428219
DOI: 10.1007/978-3-540-69321-5_20
URI: http://dx.doi.org/10.1007/978-3-540-69321-5_20
Other: Local-ID: C125756E0038A185-DAAFB03E8B94B2F7C125753F00545E1E-Schultz2008DAGM
 Degree: -

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Title: Untitled Event
Place of Event: Munich, Germany
Start-/End Date: 2008-06-10 - 2008-06-13

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Title: Pattern Recognition : 30th DAGM Symposium
Source Genre: Proceedings
 Creator(s):
Rigoll, Gerhard, Editor
Affiliations:
-
Publ. Info: Berlin : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 193 - 202 Identifier: ISBN: 978-3-540-69320-8

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Title: Lecture Notes in Computer Science
Source Genre: Series
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Publ. Info: -
Pages: - Volume / Issue: 5096 Sequence Number: - Start / End Page: - Identifier: -