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Combining band-frequency separation and deep neural network for optoacoustic imaging

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Optoacoustic Imaging: Combining Band-Frequency Separation and FD-UNet

The oficial pytorch implementation of the paper Combining banb-frequency separation and deep neural network for optoacoustic imaging

We proposed an deep FD-UNet architecture that directly exploits the frequency content in the broadband sinogram of an optoacustic measured signal for image reconstruction. The reconstructed images present a high degree of fidelity.

plot Figure: Reconstruction example. In the second half it is shown the average power spectrum of the full sinogram and the components associated with x1 and x2.

Citation

If our implementation helps your research work, please consider citing us:

@article{gonzalez2022,
  title={Combining banb-frequency separation and deep neural network for optoacoustic imaging},
  author={M. Gonzalez, M. Vera, L. Rey Vega},
  journal={arXiv preprint arXiv:2210.08099v2},
  year={2022}
}

Contact

If you have any question, please contact mggonza@fi.uba.ar or lrey@fi.uba.ar

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