Buchmann J, Kaplan BA, Powell S, Prohaska S, Laufer J. Three-dimensional quantitative photoacoustic tomography using an adjoint radiance Monte Carlo model and gradient descent.
J Biomed Opt 2019;
24:1-13. [PMID:
31172727 PMCID:
PMC6977014 DOI:
10.1117/1.jbo.24.6.066001]
[Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Accepted: 04/24/2019] [Indexed: 05/18/2023]
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 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.
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