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Three-dimensional quantitative photoacoustic tomography using an adjoint radiance Monte Carlo model and gradient descent

Research output: Contribution to journalArticle

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Three-dimensional quantitative photoacoustic tomography using an adjoint radiance Monte Carlo model and gradient descent. / Buchmann, Jens; Kaplan, Bernhard; Powell, Samuel; Prohaska, Steffen; Laufer, Jan; Kaplan, Bernhard A.

In: Journal of Biomedical Optics, Vol. 24, No. 6, 066001, 30.06.2019, p. 1-13.

Research output: Contribution to journalArticle

Harvard

Buchmann, J, Kaplan, B, Powell, S, Prohaska, S, Laufer, J & Kaplan, BA 2019, 'Three-dimensional quantitative photoacoustic tomography using an adjoint radiance Monte Carlo model and gradient descent', Journal of Biomedical Optics, vol. 24, no. 6, 066001, pp. 1-13. https://doi.org/10.1117/1.JBO.24.6.066001

APA

Buchmann, J., Kaplan, B., Powell, S., Prohaska, S., Laufer, J., & Kaplan, B. A. (2019). Three-dimensional quantitative photoacoustic tomography using an adjoint radiance Monte Carlo model and gradient descent. Journal of Biomedical Optics, 24(6), 1-13. [066001]. https://doi.org/10.1117/1.JBO.24.6.066001

Vancouver

Buchmann J, Kaplan B, Powell S, Prohaska S, Laufer J, Kaplan BA. Three-dimensional quantitative photoacoustic tomography using an adjoint radiance Monte Carlo model and gradient descent. Journal of Biomedical Optics. 2019 Jun 30;24(6):1-13. 066001. https://doi.org/10.1117/1.JBO.24.6.066001

Author

Buchmann, Jens ; Kaplan, Bernhard ; Powell, Samuel ; Prohaska, Steffen ; Laufer, Jan ; Kaplan, Bernhard A. / Three-dimensional quantitative photoacoustic tomography using an adjoint radiance Monte Carlo model and gradient descent. In: Journal of Biomedical Optics. 2019 ; Vol. 24, No. 6. pp. 1-13.

Bibtex Download

@article{fc5b634ab45d4bf79f59594d3c71053a,
title = "Three-dimensional quantitative photoacoustic tomography using an adjoint radiance Monte Carlo model and gradient descent",
abstract = "Quantitative photoacoustic tomography aims to recover maps of the local concentrations of tissue chromophores from multispectral images. While model-based inversion schemes are promising approaches, major challenges to their practical implementation include the unknown fluence distribution and the scale of the inverse problem. We describe an inversion scheme based on a radiance Monte Carlo model and an adjoint-assisted gradient optimization that incorporates fluence-dependent step sizes and adaptive moment estimation. The inversion is shown to recover absolute chromophore concentrations, blood oxygen saturation, and the Gr{\"u}neisen parameter from in silico three-dimensional phantom images for different radiance approximations. The scattering coefficient is assumed to be homogeneous and known a priori.",
keywords = "Monte Carlo, blood oxygen saturation, inverse problem, model based inversion, quantitative photoacoustic imaging, spectral unmixing",
author = "Jens Buchmann and Bernhard Kaplan and Samuel Powell and Steffen Prohaska and Jan Laufer and Kaplan, {Bernhard A.}",
year = "2019",
month = jun,
day = "30",
doi = "10.1117/1.JBO.24.6.066001",
language = "English",
volume = "24",
pages = "1--13",
journal = "Journal of Biomedical Optics",
issn = "1083-3668",
publisher = "SPIE",
number = "6",

}

RIS (suitable for import to EndNote) Download

TY - JOUR

T1 - Three-dimensional quantitative photoacoustic tomography using an adjoint radiance Monte Carlo model and gradient descent

AU - Buchmann, Jens

AU - Kaplan, Bernhard

AU - Powell, Samuel

AU - Prohaska, Steffen

AU - Laufer, Jan

AU - Kaplan, Bernhard A.

PY - 2019/6/30

Y1 - 2019/6/30

N2 - Quantitative photoacoustic tomography aims to recover maps of the local concentrations of tissue chromophores from multispectral images. While model-based inversion schemes are promising approaches, major challenges to their practical implementation include the unknown fluence distribution and the scale of the inverse problem. We describe an inversion scheme based on a radiance Monte Carlo model and an adjoint-assisted gradient optimization that incorporates fluence-dependent step sizes and adaptive moment estimation. The inversion is shown to recover absolute chromophore concentrations, blood oxygen saturation, and the Grüneisen parameter from in silico three-dimensional phantom images for different radiance approximations. The scattering coefficient is assumed to be homogeneous and known a priori.

AB - Quantitative photoacoustic tomography aims to recover maps of the local concentrations of tissue chromophores from multispectral images. While model-based inversion schemes are promising approaches, major challenges to their practical implementation include the unknown fluence distribution and the scale of the inverse problem. We describe an inversion scheme based on a radiance Monte Carlo model and an adjoint-assisted gradient optimization that incorporates fluence-dependent step sizes and adaptive moment estimation. The inversion is shown to recover absolute chromophore concentrations, blood oxygen saturation, and the Grüneisen parameter from in silico three-dimensional phantom images for different radiance approximations. The scattering coefficient is assumed to be homogeneous and known a priori.

KW - Monte Carlo

KW - blood oxygen saturation

KW - inverse problem

KW - model based inversion

KW - quantitative photoacoustic imaging

KW - spectral unmixing

UR - http://www.scopus.com/inward/record.url?scp=85067420607&partnerID=8YFLogxK

U2 - 10.1117/1.JBO.24.6.066001

DO - 10.1117/1.JBO.24.6.066001

M3 - Article

VL - 24

SP - 1

EP - 13

JO - Journal of Biomedical Optics

JF - Journal of Biomedical Optics

SN - 1083-3668

IS - 6

M1 - 066001

ER -

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