Tick, J;
Pulkkinen, A;
Tarvainen, T;
(2020)
Modelling of errors due to speed of sound variations in photoacoustic tomography using a Bayesian framework.
Biomedical Physics & Engineering Express
, 6
(1)
, Article 015003. 10.1088/2057-1976/ab57d1.
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Abstract
Inverse problem of estimating initial pressure in photoacoustic tomography is ill-posed and thus sensitive to errors in modelling and measurements. In practical experiments, accurate knowledge of the speed of sound of the imaged target is commonly not available, and therefore an approximate speed of sound is used in the computational model. This can result in errors in the solution of the inverse problem that can appear as artefacts in the reconstructed images. In this paper, the inverse problem of photoacoustic tomography is approached in a Bayesian framework. Errors due to uncertainties in the speed of sound are modelled using Bayesian approximation error modelling. Estimation of the initial pressure distribution together with information on the reliability of these estimates are considered. The approach was studied using numerical simulations. The results show that uncertainties in the speed of sound can cause significant errors in the solution of the inverse problem. However, modelling of these uncertainties improves the accuracy of the solution.
| Type: | Article |
|---|---|
| Title: | Modelling of errors due to speed of sound variations in photoacoustic tomography using a Bayesian framework |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1088/2057-1976/ab57d1 |
| Publisher version: | https://doi.org/10.1088/2057-1976/ab57d1 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| 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 |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10089804 |
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