Score-based diffusion models can be used to solve the ill-posed inverse problem of reconstructing photoacoustic tomography images from limited sensor measurements.
The proposed DensePANet model employs a novel FD-UNet++ architecture in its generator to significantly improve the reconstruction performance of photoacoustic tomography images from sparse data.