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Prakash, J. ; Mandal, S. ; Razansky, D. ; Ntziachristos, V.

Maximum entropy based non-negative optoacoustic tomographic image reconstruction.

IEEE Trans. Bio. Med. Eng. 66, 2604-2616 (2019)
Postprint DOI PMC
Open Access Green
Objective: Optoacoustic (photoacoustic) tomography is aimed at reconstructing maps of the initial pressure rise induced by the absorption of light pulses in tissue. In practice, due to inaccurate assumptions in the forward model, noise, and other experimental factors, the images are often afflicted by artifacts, occasionally manifested as negative values. The aim of this work is to develop an inversion method which reduces the occurrence of negative values and improves the quantitative performance of optoacoustic imaging. Methods: We present a novel method for optoacoustic tomography based on an entropy maximization algorithm, which uses logarithmic regularization for attaining non-negative reconstructions. The reconstruction image quality is further improved using structural prior-based fluence correction. Results: We report the performance achieved by the entropy maximization scheme on numerical simulation, experimental phantoms, and in-vivo samples. Conclusion: The proposed algorithm demonstrates superior reconstruction performance by delivering non-negative pixel values with no visible distortion of anatomical structures. Significance: Our method can enable quantitative optoacoustic imaging, and has the potential to improve preclinical and translational imaging applications.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Optical Parameters ; Photoacoustic Tomography ; Inverse Problems ; Image Reconstruction ; Regularization Theory; Photoacoustic Tomography; Optical-absorption; Regularization; Inversion; Distributions; Oxygenation; Tissues
Sprache englisch
Veröffentlichungsjahr 2019
HGF-Berichtsjahr 2019
ISSN (print) / ISBN 0018-9294
e-ISSN 0096-0616
Zeitschrift IEEE Transactions on Bio-Medical Electronics
Quellenangaben Band: 66, Heft: 9, Seiten: 2604-2616 Artikelnummer: , Supplement: ,
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Verlagsort New York, NY
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
DOI 10.1109/TBME.2019.2892842
WOS ID WOS:000482580800019
PubMed ID 30640596
Erfassungsdatum 2019-03-14
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