  Multislice ptychography is a high-resolution microscopy technique used to
image multiple separate axial planes using a single illumination direction.
However, multislice ptychography reconstructions are often degraded by
crosstalk, where some features on one plane erroneously contribute to the
reconstructed image of another plane. Here, we demonstrate the use of a
modified "double deep image prior" (DDIP) architecture in mitigating crosstalk
artifacts in multislice ptychography. Utilizing the tendency of generative
neural networks to produce natural images, a modified DDIP method yielded good
results on experimental data. For one of the datasets, we show that using DDIP
could remove the need of using additional experimental data, such as from x-ray
fluorescence, to suppress the crosstalk. Our method may help x-ray multislice
ptychography work for more general experimental scenarios.
