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Ding, L ; Dean-Ben, X.L. ; Burton, N.C.B.* ; Sobol, R.W.* ; Ntziachristos, V. ; Razansky, D.

Constrained inversion and spectral unmixing in multispectral optoacoustic tomography.

IEEE Trans. Med. Imaging 36, 1676-1685 (2017)
Postprint DOI PMC
Open Access Green
Accurate extraction of physical and biochemical parameters from optoacoustic images is often impeded due to the use of unrigorous inversion schemes, incomplete tomographic detection coverage or other experimental factors that cannot be readily accounted for during the image acquisition and reconstruction process. For instance, inaccurate assumptions in the physical forward model may lead to negative optical absorption values in the reconstructed images. Any artifacts present in the single wavelength optoacoustic images can be significantly aggravated when performing a two-step reconstruction consisting in acoustic inversion and spectral unmixing aimed at rendering the distributions of spectrally-distinct absorbers. We investigate a number of algorithmic strategies with non-negativity constraints imposed at the different phases of the reconstruction process. Performance is evaluated in cross-sectional multispectral optoacoustic tomography (MSOT) recordings from tissue-mimicking phantoms and in vivo mice embedded with varying concentrations of contrast agents. Additional in vivo validation is subsequently performed with molecular imaging data involving subcutaneous tumors labeled with genetically-expressed iRFP proteins and organ perfusion by optical contrast agents. It is shown that constrained reconstruction is essential for reducing the critical image artifacts associated with inaccurate modeling assumptions. Furthermore, imposing the non-negativity constraint directly on the unmixed distribution of the probe of interest was found to maintain the most robust and accurate reconstruction performance in all experiments.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Optoacoustic/photoacoustic Tomography ; Multispectral Imaging ; Spectral Unmixing ; Non-negative Constraint; In-vivo; Fluorescent Proteins; Reconstruction Algorithm; Least-squares; Normalization; Visualization; Oxygenation; Tissues; Media
Sprache englisch
Veröffentlichungsjahr 2017
HGF-Berichtsjahr 2017
ISSN (print) / ISBN 0278-0062
e-ISSN 1558-254X
Zeitschrift IEEE Transactions on Medical Imaging
Quellenangaben Band: 36, Heft: 8, Seiten: 1676-1685 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-505590-001
G-505500-001
DOI 10.1109/TMI.2017.2686006
WOS ID WOS:000407344800013
Scopus ID 85029351182
PubMed ID 28333622
Erfassungsdatum 2017-04-25
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