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Image reconstruction in cross-sectional optoacoustic tomography based on non-negative constrained model-based inversion.

Proc. SPIE 9539:953919 (2015)
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Open Access Green as soon as Postprint is submitted to ZB.
In optoacoustic tomography, images representing the light absorption distribution are reconstructed from the measured acoustic pressure waves at several locations around the imaged sample. Most reconstruction algorithms typically yield negative absorption values due to modelling inaccuracies and imperfect measurement conditions. Those negative optical absorption values have no physical meaning and their presence hinders image quantification and interpretation of biological information. We investigate herein the performance of optimization methods that impose non-negative constraints in model-based optoacoustic inversion. Specifically, we analyze the effects of the non-negative restrictions on image quality and accuracy as compared to the unconstrained approach. An efficient algorithm based on the projected quasi-Newton scheme and the limitedmemory Broyden-Fletcher-Goldfarb-Shannon method is used for the non-negative constrained inversion. We showcase that imposing non-negative constraints in model-based reconstruction leads to a quality increase in cross-sectional tomographic optoacoustic images.CCC.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Model-based Inversion ; Non-negative Constrained Least Squares ; Optoacoustic Tomography ; Photoacoustic Tomography
Language english
Publication Year 2015
HGF-reported in Year 2015
ISSN (print) / ISBN 0277-786X
e-ISSN 1996-756X
Book Volume Title Opto-Acoustic Methods and Applications in Biophotonics II
Conference Date 22-23 June 2015
Conference Location München
Quellenangaben Volume: 9539, Issue: , Pages: , Article Number: 953919 Supplement: ,
Publisher SPIE
Reviewing status Peer reviewed
POF-Topic(s) 30205 - Bioengineering and Digital Health
Research field(s) Enabling and Novel Technologies
PSP Element(s) G-505500-001
G-505590-001
Scopus ID 85165749934
Scopus ID 85019504744
Scopus ID 85017014223
Erfassungsdatum 2017-06-01