Image reconstruction with noise and error modelling in quantitative photoacoustic tomography

Tanja Tarvainen; Aki Pulkkinen; Ben T. Cox; Jari P. Kaipio; Simon R. Arridge

doi:10.1117/12.2209477

15 March 2016 Image reconstruction with noise and error modelling in quantitative photoacoustic tomography

Tanja Tarvainen, Aki Pulkkinen, Ben T. Cox, Jari P. Kaipio, Simon R. Arridge

Proceedings Volume 9708, Photons Plus Ultrasound: Imaging and Sensing 2016; 97083Q (2016) https://doi.org/10.1117/12.2209477
Event: SPIE BiOS, 2016, San Francisco, California, United States

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.

Citation Download Citation

Tanja Tarvainen, Aki Pulkkinen, Ben T. Cox, Jari P. Kaipio, and Simon R. Arridge "Image reconstruction with noise and error modelling in quantitative photoacoustic tomography", Proc. SPIE 9708, Photons Plus Ultrasound: Imaging and Sensing 2016, 97083Q (15 March 2016); https://doi.org/10.1117/12.2209477

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