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Fourier Neural Operator Networks: A Fast and General Solver for the Photoacoustic Wave Equation
Simulation tools for photoacoustic wave propagation have played a key role in advancing photoacoustic imaging by providing quantitative and qualitative insights into parameters affecting image quality.
Dense Dilated UNet: Deep Learning for 3D Photoacoustic Tomography Image Reconstruction
We compare the proposed CNN in terms of image quality as measured by the multiscale structural similarity index metric to the Fully Dense UNet (FD-UNet).
Limited View and Sparse Photoacoustic Tomography for Neuroimaging with Deep Learning
Photoacoustic tomography (PAT) is a nonionizing imaging modality capable of acquiring high contrast and resolution images of optical absorption at depths greater than traditional optical imaging techniques.
Fully Dense UNet for 2D Sparse Photoacoustic Tomography Artifact Removal
Photoacoustic imaging is an emerging imaging modality that is based upon the photoacoustic effect.
