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Feature Tracking for High Speed AFM Imaging of Biopolymers.

Brett HartmanSean B Andersson
Published in: International journal of molecular sciences (2018)
The scanning speed of atomic force microscopes continues to advance with some current commercial microscopes achieving on the order of one frame per second and at least one reaching 10 frames per second. Despite the success of these instruments, even higher frame rates are needed with scan ranges larger than are currently achievable. Moreover, there is a significant installed base of slower instruments that would benefit from algorithmic approaches to increasing their frame rate without requiring significant hardware modifications. In this paper, we present an experimental demonstration of high speed scanning on an existing, non-high speed instrument, through the use of a feedback-based, feature-tracking algorithm that reduces imaging time by focusing on features of interest to reduce the total imaging area. Experiments on both circular and square gratings, as well as silicon steps and DNA strands show a reduction in imaging time by a factor of 3-12 over raster scanning, depending on the parameters chosen.
Keyphrases
  • high speed
  • high resolution
  • atomic force microscopy
  • machine learning
  • deep learning
  • mass spectrometry
  • single molecule
  • computed tomography
  • electron microscopy
  • cell free