A bayesian approach to eigenspectra optoacoustic tomography.
IEEE Trans. Med. Imaging 37, 2070-2079 (2018)
The quantification of hemoglobin oxygen saturation (sO(2)) with multispectral optoacoustic (OA) (photoacoustic) tomography (MSOT) is a complex spectral unmixing problem, since the OA spectra of hemoglobin are modified with tissue depth due to depth (location) and wavelength dependencies of optical fluence in tissue. In a recent work, a method termed eigenspectra MSOT (eMSOT) was proposed for addressing the dependence of spectra on fluence and quantifying blood sO(2) in deep tissue. While eMSOT offers enhanced sO(2) quantification accuracy over conventional unmixing methods, its performance may be compromised by noise and image reconstruction artifacts. In this paper, we propose a novel Bayesian method to improve eMSOT performance in noisy environments. We introduce a spectral reliability map, i.e., a method that can estimate the level of noise superimposed onto the recorded OA spectra. Using this noise estimate, we formulate eMSOT as a Bayesian inverse problem where the inversion constraints are based on probabilistic graphical models. Results based on numerical simulations indicate that the proposed method offers improved accuracy and robustness under high noise levels due the adaptive nature of the Bayesian method.
Impact Factor
Scopus SNIP
Web of Science
Times Cited
Scopus
Cited By
Altmetric
Publication type
Article: Journal article
Document type
Scientific Article
Thesis type
Editors
Keywords
Optoacoustic/photoacoustic Imaging ; Multispectral Optoacoustic Tomography ; Photoacoustic Tomography ; Bayesian Methods ; Oxygen Saturation ; Spectral Unmixing; Quantitative Photoacoustic Tomography; Image-reconstruction; Model; Distributions; Challenges; Deep; Map
Keywords plus
Language
Publication Year
2018
Prepublished in Year
HGF-reported in Year
2018
ISSN (print) / ISBN
0278-0062
e-ISSN
1558-254X
ISBN
Book Volume Title
Conference Title
Conference Date
Conference Location
Proceedings Title
Quellenangaben
Volume: 37,
Issue: 9,
Pages: 2070-2079
Article Number: ,
Supplement: ,
Series
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publishing Place
New York, NY [u.a.]
Day of Oral Examination
0000-00-00
Advisor
Referee
Examiner
Topic
University
University place
Faculty
Publication date
0000-00-00
Application date
0000-00-00
Patent owner
Further owners
Application country
Patent priority
Reviewing status
Peer reviewed
POF-Topic(s)
30205 - Bioengineering and Digital Health
Research field(s)
Enabling and Novel Technologies
PSP Element(s)
G-505500-001
Grants
Copyright
Erfassungsdatum
2018-05-07