  Traditional image acquisition for cryo focused ion-beam scanning electron
microscopy tomography often sees thousands of images being captured over a
period of many hours, with immense data sets being produced. When imaging beam
sensitive materials, these images are often compromised by additional
constraints related to beam damage and the devitrification of the material
during imaging, which renders data acquisition both costly and unreliable.
Subsampling and inpainting are proposed as solutions for both of these aspects,
allowing fast and low-dose imaging to take place in the FIB-SEM without an
appreciable low in image quality. In this work, experimental data is presented
which validates subsampling and inpainting as a useful tool for convenient and
reliable data acquisition in a FIB-SEM, with new methods of handling
3-dimensional data being employed in context of dictionary learning and
inpainting algorithms using a newly developed microscope control software and
data recovery algorithm.
