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9 March 2023 Utilizing variational autoencoders in photoacoustic tomography
Teemu Sahlström, Tanja Tarvainen
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Proceedings Volume 12379, Photons Plus Ultrasound: Imaging and Sensing 2023; 1237914 (2023) https://doi.org/10.1117/12.2644801
Event: SPIE BiOS, 2023, San Francisco, California, United States
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Abstract
In the inverse problem of photoacoustic tomography (PAT), initial pressure distribution induced by the photoa-coustic effect is estimated from a set of measured ultrasound data. In the recent decade, utilization of various deep learning approaches for the inverse problem of PAT have been proposed. However, many of these approaches do not provide information of the uncertainties of the reconstructed images. In this work, we propose a deep learning based approach for the Bayesian inverse problem of PAT based on variational autoencoders. The approach is evaluated using numerical simulations and compared against posterior distribution obtained using a conventional Bayesian image reconstruction approach. The approach is shown to provide rapid and accurate reconstructions with reliability estimates.
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Teemu Sahlström and Tanja Tarvainen "Utilizing variational autoencoders in photoacoustic tomography", Proc. SPIE 12379, Photons Plus Ultrasound: Imaging and Sensing 2023, 1237914 (9 March 2023); https://doi.org/10.1117/12.2644801
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KEYWORDS
Neural networks
Inverse problems
Deep learning
Bayesian inference
Photoacoustic tomography
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