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Scale-Covariant and Scale-Invariant Gaussian Derivative Networks Read chapter Read first chapter

2021 | OriginalPaper | Chapter

Challenges for Optical Flow Estimates in Elastography

Authors : Ekaterina Sherina, Lisa Krainz, Simon Hubmer, Wolfgang Drexler, Otmar Scherzer

Published in: Scale Space and Variational Methods in Computer Vision

Publisher: Springer International Publishing

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Abstract

In this paper, we consider visualization of displacement fields via optical flow methods in elastographic experiments consisting of a static compression of a sample. We propose an elastographic optical flow method (EOFM) which takes into account experimental constraints, such as appropriate boundary conditions, the use of speckle information, as well as the inclusion of structural information derived from knowledge of the background material. We present numerical results based on both simulated and experimental data from an elastography experiment in order to demonstrate the relevance of our proposed approach.

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previous chapter Multiscale Registration
next chapter An Anisotropic Selection Scheme for Variational Optical Flow Methods with Order-Adaptive Regularisation
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Metadata
Title
Challenges for Optical Flow Estimates in Elastography
Authors
Ekaterina Sherina
Lisa Krainz
Simon Hubmer
Wolfgang Drexler
Otmar Scherzer
Copyright Year
2021
Book
Scale Space and Variational Methods in Computer Vision

Print ISBN: 978-3-030-75548-5

Electronic ISBN: 978-3-030-75549-2

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-75549-2_11

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