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

Using a modified double deep image prior for crosstalk mitigation in multislice ptychography