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Image reconstruction with noise and error modelling in quantitative photoacoustic tomography

Tarvainen, T; Pulkkinen, A; Cox, BT; Kaipio, JP; Arridge, SR; (2016) Image reconstruction with noise and error modelling in quantitative photoacoustic tomography. In: Oraevsky, AA and Wang, LV, (eds.) Photons Plus Ultrasound: Imaging and Sensing 2016. SPIE: San Francisco, CA, USA. Green open access

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Abstract

Quantitative photoacoustic tomography is an emerging imaging technique aimed at estimating the optical parameters inside tissue from photoacoustic images. The method proceeds from photoacoustic tomography by taking the estimated initial pressure distributions as data and estimating the absolute values of the optical parameters. Therefore, both the data and the noise of the second (optical) inverse problem are affected by the method applied to solve the first (acoustic) inverse problem. In this work, the Bayesian approach for quantitative photoacoustic tomography is taken. Modelling of noise and errors and incorporating their statistics into the solution of the inverse problem are investigated.

Type: Proceedings paper
Title: Image reconstruction with noise and error modelling in quantitative photoacoustic tomography
Event: SPIE BIOS
Location: San Francisco, CA
Dates: 14 February 2016 - 17 February 2016
Open access status: An open access version is available from UCL Discovery
DOI: 10.1117/12.2209477
Publisher version: https://doi.org/10.1117/12.2209477
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Photoacoustic tomography, quantitative imaging, inverse problems, Bayesian methods
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 Computer 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/10113877
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