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Statistical independence in nonlinear model-based inversion for quantitative photoacoustic tomography

An, L; Saratoon, T; Fonseca, M; Ellwood, R; Cox, B; (2017) Statistical independence in nonlinear model-based inversion for quantitative photoacoustic tomography. Biomedical Optics Express , 8 (11) pp. 5297-5310. 10.1364/BOE.8.005297. Green open access

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Abstract

The statistical independence between the distributions of different chromophores in tissue has previously been used for linear unmixing with independent component analysis (ICA). In this study, we propose exploiting this statistical property in a nonlinear model-based inversion method. The aim is to reduce the sensitivity of the inversion scheme to errors in the modelling of the fluence, and hence provide more accurate quantification of the concentration of independent chromophores. A gradient-based optimisation algorithm is used to minimise the error functional, which includes a term representing the mutual information between the chromophores in addition to the standard least-squares data error. Both numerical simulations and an experimental phantom study are conducted to demonstrate that, in the presence of experimental errors in the fluence model, the proposed inversion method results in more accurate estimation of the concentrations of independent chromophores compared to the standard model-based inversion.

Type: Article
Title: Statistical independence in nonlinear model-based inversion for quantitative photoacoustic tomography
Open access status: An open access version is available from UCL Discovery
DOI: 10.1364/BOE.8.005297
Publisher version: http://doi.org/10.1364/BOE.8.005297
Language: English
Additional information: © 2017 Optical Society of America. Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10040496
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