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Lutzweiler, C. ; Tzoumas, S. ; Rosenthal, A. ; Ntziachristos, V. ; Razansky, D.

High-throughput sparsity-based inversion scheme for optoacoustic tomography.

IEEE Trans. Med. Imaging 35, 674-684 (2016)
DOI PMC
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
The concept of sparsity is extensively exploited in the fields of data acquisition and image processing, contributing to better signal-to-noise and spatio-temporal performance of the various imaging methods. In the field of optoacoustic tomography, the image reconstruction problem is often characterized by computationally extensive inversion of very large datasets, for instance when acquiring volumetric multispectral data with high temporal resolution. In this article we seek to accelerate accurate model-based optoacoustic inversions by identifying various sources of sparsity in the forward and inverse models as well as in the single- and multi-frame representation of the projection data. These sources of sparsity are revealed through appropriate transformations in the signal, model and image domains and are subsequently exploited for expediting image reconstruction. The sparsity-based inversion scheme was tested with experimental data, offering reconstruction speed enhancement by a factor of 40 to 700 times as compared with the conventional iterative model-based inversions while preserving similar image quality. The demonstrated results pave the way for achieving real-time performance of model-based reconstruction in multi-dimensional optoacoustic imaging.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Inverse Problems ; Optoacoustic/photoacoustic Imaging ; Tomography ; Image Reconstruction ; Sparse Signal Representation; Iterative Image-reconstruction; Photoacoustic Tomography; Algorithm; Pet; Mri
Sprache englisch
Veröffentlichungsjahr 2016
Prepublished im Jahr 2015
HGF-Berichtsjahr 2015
ISSN (print) / ISBN 0278-0062
e-ISSN 1558-254X
Zeitschrift IEEE Transactions on Medical Imaging
Quellenangaben Band: 35, Heft: 2, Seiten: 674-684 Artikelnummer: , Supplement: ,
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Verlagsort New York, NY [u.a.]
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Biological and Medical Imaging (IBMI)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-505500-001
G-505590-001
PubMed ID 26469127
DOI 10.1109/TMI.2015.2490799
WOS ID WOS:000370745600028
Erfassungsdatum 2015-11-04
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