Paper Info
Title
Multiscale Factorization Of The Wave Equation With Application To Compressed Sensing Photoacoustic Tomography
Abstract
Performing a large number of spatial measurements enables high-resolution photoacoustic imaging without specific prior information. However, the acquisition of spatial measurements is time-consuming, costly, and technically challenging. By exploiting nonlinear prior information, compressed sensing techniques in combination with sophisticated reconstruction algorithms allow reducing the number of measurements while maintaining high spatial resolution. To this end, in this work we propose a multiscale factorization for the wave equation that decomposes the measured data into a low-frequency factor and sparse high-frequency factors. By extending the acoustic reciprocity principle, we transfer sparsity in the measurement domain into spatial sparsity of the initial pressure, which allows the use of sparse reconstruction techniques. Numerical results are presented that demonstrate the feasibility of the proposed framework.
Year
DOI
Venue
2021
10.1137/20M1356154
SIAM JOURNAL ON IMAGING SCIENCES
Keywords
DocType
Volume
photoacoustic tomography, image reconstruction, limited data, wave equation, cost reduction, compressed sensing, multiscale factorization
Journal
14
Issue
ISSN
Citations 
2
1936-4954
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Gerhard Zangerl100.34
Markus Haltmeier27414.16