@inproceedings{discovery10050439,
          series = {PROCEEDINGS SPIE BIOS},
           month = {January},
       publisher = {SPIE},
           title = {Photoacoustic image reconstruction in Bayesian framework},
            year = {2018},
         journal = {Progress in Biomedical Optics and Imaging - Proceedings of SPIE},
          volume = {10494},
         address = {San Francisco, California, United States},
            note = {This version is the version of record. For information on re-use, please refer to the publisher's terms and conditions.},
       booktitle = {Proceedings Volume 10494, Photons Plus Ultrasound: Imaging and Sensing 2018; 1049450 (2018)},
          editor = {Alexander A. Oraevsky, and Lihong V. Wang},
          author = {Tick, J and Pulkkinen, A and Lucka, F and Ellwood, R and Cox, BT and Arridge, SR and Tarvainen, T},
            issn = {1605-7422},
        abstract = {The photoacoustic image reconstruction problem (inverse problem) is to estimate an initial acoustic pressure distribution from measurements of ultrasound waves generated within an object due to optical excitation with a short light pulse. In this work, the recently suggested Bayesian approach to photoacoustic tomography is extended to three dimensions and an iterative matrix-free method for the solution of the problem is described. Image reconstruction is investigated with numerical simulations and experimental data. The use of different prior information and noise models in different sensor geometries, including a limited-view setup, is investigated. The results show that the Bayesian approach can produce accurate estimates of the initial pressure distribution even in a limited-view setup provided that prior information and the noise have been properly modelled.},
             url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10494/2288163/Photoacoustic-image-reconstruction-in-Bayesian-framework/10.1117/12.2288163.full?SSO=1},
        keywords = {photoacoustic tomography, inverse problems, Bayesian methods}
}