Nicholls, Daniel 
ORCID: 0000-0003-1677-701X, Wells, Jack, Robinson, Alex W ORCID: 0000-0002-1901-2509, Moshtaghpour, Amirafshar ORCID: 0000-0002-6751-2698, Kobylynska, Maryna, Fleck, Roland A, Kirkland, Angus I and Browning, Nigel D ORCID: 0000-0003-0491-251X
(2022)
A Targeted Sampling Strategy for Compressive Cryo Focused Ion Beam
Scanning Electron Microscopy.
[Preprint]
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2211.03494v1.pdf - Published version Download (8MB) | Preview |
Abstract
Cryo Focused Ion-Beam Scanning Electron Microscopy (cryo FIB-SEM) enables three-dimensional and nanoscale imaging of biological specimens via a slice and view mechanism. The FIB-SEM experiments are, however, limited by a slow (typically, several hours) acquisition process and the high electron doses imposed on the beam sensitive specimen can cause damage. In this work, we present a compressive sensing variant of cryo FIB-SEM capable of reducing the operational electron dose and increasing speed. We propose two Targeted Sampling (TS) strategies that leverage the reconstructed image of the previous sample layer as a prior for designing the next subsampling mask. Our image recovery is based on a blind Bayesian dictionary learning approach, i.e., Beta Process Factor Analysis (BPFA). This method is experimentally viable due to our ultra-fast GPU-based implementation of BPFA. Simulations on artificial compressive FIB-SEM measurements validate the success of proposed methods: the operational electron dose can be reduced by up to 20 times. These methods have large implications for the cryo FIB-SEM community, in which the imaging of beam sensitive biological materials without beam damage is crucial.
| Item Type: | Preprint |
|---|---|
| Additional Information: | Submitted to ICASSP 2023 |
| Uncontrolled Keywords: | eess.SP, eess.SP, cs.LG |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 16 Nov 2022 15:29 |
| Last Modified: | 18 Jan 2023 19:43 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3166233 |
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