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Traditional image acquisition for cryo focused ion-beam scanning electronmicroscopy tomography often sees thousands of images being captured over aperiod of many hours, with immense data sets being produced. When imaging beamsensitive materials, these images are often compromised by additionalconstraints related to beam damage and the devitrification of the materialduring 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 anappreciable low in image quality. In this work, experimental data is presentedwhich validates subsampling and inpainting as a useful tool for convenient andreliable data acquisition in a FIB-SEM, with new methods of handling3-dimensional data being employed in context of dictionary learning andinpainting algorithms using a newly developed microscope control software anddata recovery algorithm.

The Potential of Subsampling and Inpainting for Fast Low-Dose Cryo FIB-SEM Imaging and Tomography