Introducing measure-by-wire, the systematic use of systems and control theory in transmission electron microscopy

Tejada, Arturo; Dekker, Arnold J. den; Broek, Wouter Van den

doi:10.1016/j.ultramic.2011.08.011

Cited by 16 publications

(10 citation statements)

References 30 publications

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“…EXAMPLE Transmission electron microscopes (TEMs) are the tools of choice for nanotechnology and biological research since they can reveal information on the internal structure of a wide range of specimens. Although currently, most of these microscopes are operated manually, it is expected that in the near future autonomous TEMs will be needed to perform high-throughput nano-measurements [23]. One aspect of TEM automation that requires special attention is that of image drift compensation (see, e.g., [24]).…”

Section: B Stability and Performance Of Dual-random-rate Systemsmentioning

confidence: 99%

Stability and performance analysis of dual-random-rate systems via Markov jump linear system theory

Tejada

Chávez‐Fuentes

Vos

2011

IEEE Conference on Decision and Control and European Control Conference

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This paper introduces the class of dual-randomrate systems (i.e., dual-rate systems with random output rates), which is well suited to model image-based control systems. It is shown that a dual-random-rate system can be reformulated as a switched linear system with a (quasi-periodic) random switching signal that is a static function of Markov chain. This reformulation makes it possible to study dual-random-rate systems with the stability and output performance analysis tools developed for Markov jump linear systems. The approach is illustrated via a practical example: the compensation of image drift in a transmission electron microscope.

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Section: B Stability and Performance Of Dual-random-rate Systemsmentioning

confidence: 99%

Stability and performance analysis of dual-random-rate systems via Markov jump linear system theory

Tejada

Chávez‐Fuentes

Vos

2011

IEEE Conference on Decision and Control and European Control Conference

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“…In cryo-TEM, feedback from image analysis is employed to identify and judge the quality of particles for acquisition of imaging [10][11][12] or diffraction data [13][14][15] . In material science TEM, similar approaches exist that enable ultrastable imaging [16][17][18] . There is, however, no solution that incorporates advanced image analysis procedures into the various kinds of TEM data acquisition workflows in a generic way.…”

Section: Introductionmentioning

confidence: 99%

Software tools for automated transmission electron microscopy

Schorb¹,

et al. 2019

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High-throughput data collection for electron microscopy (EM) demands appropriate software tools. We present a combination of such tools that enable automated acquisition guided by image analysis for a variety of transmission EM acquisition schemes. Py-EM interfaces with the microscope control software SerialEM and expands its updated flexible automation features by image analysis to enable feedback microscopy. We demonstrate dose-reduction in cryo-EM experiments, fully automated acquisition of every cell in a plastic section, and automated targeting on serial sections for volumetric imaging across multiple grids. Author contributions M.S., I.H., W.J.H.H and Y.S. designed the experimental applications. M.S. and D.N.M. did the software development. I.H., W.J.H.H. and M.S. collected the data. All authors contributed valuable suggestions to the necessary software functionality and edited the article. M.S. and D.N.M wrote the initial manuscript.

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“…Thus, there is need of a new generation of TEMs capable of autonomously performing and reporting highthroughput nano-scale measurements. As was recently suggested, such TEMs could be developed with the aid of systems and control concepts [1].…”

Section: Introductionmentioning

confidence: 99%

Towards an adaptive minimum variance control scheme for specimen drift compensation in transmission electron microscopes

Tejada

Vos

Dekker

2011

The 2011 International Workshop on Multidimensional (nD) Systems

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Abstract-Transmission electron microscopes are the tools of choice in materials science, semiconductor, and biological research and it is expected that they will be increasingly used to autonomously perform high-volume, repetitive, nanomeasurements in the near future. Thus, there is a clear need to develop automation strategies for these microscopes.This paper introduces an adaptive minimum variance control scheme to compensate specimen drift, a common cause of image blurring in long-exposure images. The controller, which is new in the electron microscope literature, makes use of ARMASA, a statistical toolbox designed to identify linear models from finite-length data sets, to generate ARMA models of the drift process 'on-the-fly'. These models are then used as part of a controller designed to reduce the drift variance. The benefits of the proposed scheme, which can be quite substantial, are illustrated through a set of simulations that use a model of the drift present in a sequence of experimental images.

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Introducing measure-by-wire, the systematic use of systems and control theory in transmission electron microscopy

Cited by 16 publications

References 30 publications

Stability and performance analysis of dual-random-rate systems via Markov jump linear system theory

Stability and performance analysis of dual-random-rate systems via Markov jump linear system theory

Software tools for automated transmission electron microscopy

Towards an adaptive minimum variance control scheme for specimen drift compensation in transmission electron microscopes

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