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Updated: Jul 22, 2025

Measuring the Shape and Size of Activated Sludge Particles Immobilized in Agar with an Open Source Software Pipeline
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InFluence: An Open-Source Python Package to Model Images Captured with Direct Electron Detectors.

Gearóid Liam Mangan1,2, Grigore Moldovan3, Andrew Stewart2

  • 1Physics Department, Faculty of Science and Engineering, University of Limerick, Limerick V94 T9PX, Ireland.

Microscopy and Microanalysis : the Official Journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada
|July 25, 2023
PubMed
Summary
This summary is machine-generated.

A new Python package models direct electron detectors for low-dose electron microscopy. This tool aids quantitative analysis of sensitive biological and pharmaceutical materials using low-fluence imaging.

Keywords:
Monte Carlo methodsdetective quantum efficiencydirect detectorselectron microscopylow fluencemedipix3modulation transfer functionopen-source

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Area of Science:

  • Materials Science
  • Biophysics
  • Imaging Technology

Background:

  • Direct electron detectors offer high efficiency for low-fluence electron microscopy.
  • Beam-sensitive pharmaceutical and biological samples require low-dose imaging techniques.
  • Accurate modeling is crucial for quantitative analysis of low-fluence electron microscopy data.

Purpose of the Study:

  • To develop an open-source Python package for modeling single-layer direct electron detectors.
  • To enable accurate simulation of both low and high fluence imaging conditions.
  • To provide a method for experimental validation using modulation transfer function and detective quantum efficiency.

Main Methods:

  • Development of a novel open-source Python package.
  • Implementation of algorithms to model single-layer direct electron detector performance.
  • Integration of validation methods using modulation transfer function (MTF) and detective quantum efficiency (DQE).

Main Results:

  • The package accurately models direct electron detectors across various fluence levels.
  • The developed model facilitates quantitative analysis of low-fluence electron micrographs and diffraction patterns.
  • Experimental validation confirms the model's accuracy in predicting detector performance.

Conclusions:

  • The new Python package provides a robust tool for modeling direct electron detectors.
  • This facilitates improved quantitative analysis in low-dose electron microscopy for beam-sensitive materials.
  • The open-source nature promotes wider adoption and further development in the field.