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Quantitative photoacoustic tomography using forward and adjoint Monte Carlo models of radiance

Hochuli, Roman; Powell, Samuel; Arridge, Simon; Cox, Ben

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Authors

Roman Hochuli

Samuel Powell

Simon Arridge

Ben Cox



Abstract

Forward and adjoint Monte Carlo (MC) models of radiance are proposed for use in model-based quantitative photoacoustic tomography. A two-dimensional (2-D) radiance MC model using a harmonic angular basis is introduced and validated against analytic solutions for the radiance in heterogeneous media. A gradient-based optimization scheme is then used to recover 2-D absorption and scattering coefficients distributions from simulated photoacoustic measurements. It is shown that the functional gradients, which are a challenge to compute efficiently using MC models, can be calculated directly from the coefficients of the harmonic angular basis used in the forward and adjoint models. This work establishes a framework for transport-based quantitative photoacoustic tomography that can fully exploit emerging highly parallel computing architectures.

Citation

Hochuli, R., Powell, S., Arridge, S., & Cox, B. (2016). Quantitative photoacoustic tomography using forward and adjoint Monte Carlo models of radiance. Journal of Biomedical Optics, 21(12), Article 126004. https://doi.org/10.1117/1.jbo.21.12.126004

Journal Article Type Article
Acceptance Date Nov 1, 2016
Online Publication Date Dec 2, 2016
Publication Date Dec 2, 2016
Deposit Date Jan 24, 2020
Publicly Available Date Oct 2, 2020
Journal Journal of Biomedical Optics
Print ISSN 1083-3668
Publisher Society of Photo-optical Instrumentation Engineers
Peer Reviewed Peer Reviewed
Volume 21
Issue 12
Article Number 126004
DOI https://doi.org/10.1117/1.jbo.21.12.126004
Public URL https://nottingham-repository.worktribe.com/output/3791714
Publisher URL https://www.spiedigitallibrary.org/journals/journal-of-biomedical-optics/volume-21/issue-12/126004/Quantitative-photoacoustic-tomography-using-forward-and-adjoint-Monte-Carlo-models/10.1117/1.JBO.21.12.126004.full?SSO=1

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