Weighted model-based optoacoustic reconstruction for partial-view geometries.
J. Biophotonics 15:e202100334 (2022)
Acoustic heterogeneities in biological samples are known to cause artefacts in tomographic optoacoustic (photoacoustic) image reconstruction. A statistical weighted model-based reconstruction approach was previously introduced to mitigate such artefacts. However, this approach does not reliably provide high-quality reconstructions for partial-view imaging systems, which are common in preclinical and clinical optoacoustics. In this paper, the capability of the weighted model-based algorithm is extended to generate optoacoustic reconstructions with less distortions for partial-view geometry data. This is achieved by manipulating the weighting scheme based on the detector geometry. Using partial-view optoacoustic tomography data from a tissue-mimicking phantom containing a strong acoustic reflector, tumors grafted onto mice, and a mouse brain with intact skull, the proposed partial-view-corrected weighted model-based algorithm is shown to mitigate reflection artefacts in reconstructed images without distorting structures or boundaries, compared to both conventional model-based and the weighted model-based algorithms. It is also demonstrated that the partial-view-corrected weighted model-based algorithm has the additional advantage of suppressing streaking artefacts due to the partial-view geometry itself in the presence of a very strong optoacoustic chromophore. Due to its enhanced performance, the partial-view-corrected weighted model-based algorithm may prove useful for improving the quality of partial-view multispectral optoacoustic tomography, leading to enhanced visualization of functional parameters such as tissue oxygenation. This article is protected by copyright. All rights reserved.
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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Typ der Hochschulschrift
Herausgeber
Schlagwörter
Acoustic Heterogeneities ; Optoacoustic (photoacoustic) Imaging ; Partial-view Correction ; Streaking Artefacts ; Weighted Model-based Reconstruction; Image-reconstruction; Tomography
Keywords plus
Sprache
englisch
Veröffentlichungsjahr
2022
Prepublished im Jahr
HGF-Berichtsjahr
2022
ISSN (print) / ISBN
1864-063X
e-ISSN
1864-0648
ISBN
Bandtitel
Konferenztitel
Konferzenzdatum
Konferenzort
Konferenzband
Quellenangaben
Band: 15,
Heft: 6,
Seiten: ,
Artikelnummer: e202100334
Supplement: ,
Reihe
Verlag
Wiley
Verlagsort
Postfach 101161, 69451 Weinheim, Germany
Tag d. mündl. Prüfung
0000-00-00
Betreuer
Gutachter
Prüfer
Topic
Hochschule
Hochschulort
Fakultät
Veröffentlichungsdatum
0000-00-00
Anmeldedatum
0000-00-00
Anmelder/Inhaber
weitere Inhaber
Anmeldeland
Priorität
Begutachtungsstatus
Peer reviewed
POF Topic(s)
30205 - Bioengineering and Digital Health
Forschungsfeld(er)
Enabling and Novel Technologies
PSP-Element(e)
G-505500-001
G-503800-001
Förderungen
Horizon 2020 Framework Programme
FP7 People: Marie-Curie Actions
Alexander von Humboldt-Stiftung
Copyright
Erfassungsdatum
2022-06-09