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Abstract

We present an optimization framework for photo-acoustic tomography of brain based on a system of coupled equations that describe the propagation of sound waves in linear isotropic inhomogeneous and lossy elastic media with the absorption and physical dispersion following a frequency power law using fractional Laplacian operators. The adjoint of the associated continuous forward operator is derived, and a numerical framework for computing this adjoint based on a k- space pseudospectral method is presented. We analytically show that the derived continuous adjoint matches the adjoint of an associated discretised operator. We include this adjoint in a first-order positivity constrained optimization algorithm that is regularized by total variation minimization, and show that the iterates monotonically converge to a minimizer of an objective function, even in the presence of some error in estimating the physical parameters of the medium.

Details

1009240
Title
A continuous adjoint for photo-acoustic tomography of the brain
Publication title
arXiv.org; Ithaca
Publication year
2018
Publication date
Feb 12, 2018
Section
Mathematics
Publisher
Cornell University Library, arXiv.org
Source
arXiv.org
Place of publication
Ithaca
Country of publication
United States
University/institution
Cornell University Library arXiv.org
e-ISSN
2331-8422
Source type
Working Paper
Language of publication
English
Document type
Working Paper
Publication history
 
 
Online publication date
2018-07-04
Milestone dates
2018-02-12 (Submission v1)
Publication history
 
 
   First posting date
04 Jul 2018
ProQuest document ID
2073702885
Document URL
https://www.proquest.com/working-papers/continuous-adjoint-photo-acoustic-tomography/docview/2073702885/se-2?accountid=208611
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Copyright
© 2018. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2019-04-12
Database
2 databases
  • ProQuest One Academic
  • ProQuest One Academic