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Ding, L ; Dean-Ben, X.L. ; Razansky, D.

Real-time model-based inversion in cross-sectional optoacoustic tomography.

IEEE Trans. Med. Imaging 35, 1883-1891 (2016)
Postprint DOI PMC
Open Access Green
Analytical (closed-form) inversion schemes have been the standard approach for image reconstruction in optoacoustic tomography due to their fast reconstruction abilities and low memory requirements. Yet, the need for quantitative imaging and artifact reduction has led to the development of more accurate inversion approaches, which rely on accurate forward modeling of the optoacoustic wave generation and propagation. In this way, multiple experimental factors can be incorporated, such as the exact detection geometry, spatio-temporal response of the transducers, and acoustic heterogeneities. The modelbased inversion commonly results in very large sparse matrix formulations that require computationally extensive and memory demanding regularization schemes for image reconstruction, hindering their effective implementation in real-time imaging applications. Herein, we introduce a new discretization procedure for efficient model-based reconstructions in two-dimensional optoacoustic tomography that allows for parallel implementation on a graphics processing unit (GPU) with a relatively low numerical complexity. By on-the-fly calculation of the model matrix in each iteration of the inversion procedure, the new approach results in imaging frame rates exceeding 10Hz, thus enabling real-time image rendering using the model-based approach.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Model-based Reconstruction ; Optoacoustic Tomography ; Photoacoustic Tomography ; Real-time Imaging; Reconstruction Algorithm; Image-reconstruction; Photoacoustic Tomography; Acoustic Inversion; Detectors; Media
Language english
Publication Year 2016
HGF-reported in Year 2016
ISSN (print) / ISBN 0278-0062
e-ISSN 1558-254X
Journal IEEE Transactions on Medical Imaging
Quellenangaben Volume: 35, Issue: 8, Pages: 1883-1891 Article Number: , Supplement: ,
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Publishing Place New York, NY [u.a.]
Reviewing status Peer reviewed
Institute(s) Institute of Biological and Medical Imaging (IBMI)
POF-Topic(s) 30205 - Bioengineering and Digital Health
Research field(s) Enabling and Novel Technologies
PSP Element(s) G-505590-001
DOI 10.1109/TMI.2016.2536779
WOS ID WOS:000381436000009
PubMed ID 26955023
Erfassungsdatum 2016-03-17
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