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There are three types of cytoskeletal structures in eukaryotic cells—microfilaments, intermediate filaments, and microtubules. With a diameter of about 25 nm, microtubules are the thickest of these fibers. Microtubules carry out a variety of functions that include cell structure and support, transport of organelles, cell motility (movement), and the separation of chromosomes during cell division.
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Related Experiment Video

Updated: Apr 28, 2026

Simultaneous Interference Reflection and Total Internal Reflection Fluorescence Microscopy for Imaging Dynamic Microtubules and Associated Proteins
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Image simulation for biological microscopy: microlith.

Shalin B Mehta1, Rudolf Oldenbourg2

  • 1Cellular Dynamics Program, Marine Biological Laboratory, 7 MBL Street, Woods Hole, MA 02543, USA.

Biomedical Optics Express
|June 19, 2014
PubMed
Summary
This summary is machine-generated.

A new open-source toolbox, microlith, accurately simulates biological phase microscopy images. This tool reveals dark-field microscopy

Keywords:
(110.2990) Image formation theory(110.4980) Partial coherence in imaging(170.0180) Microscopy(170.3880) Medical and biological imaging(350.5030) Phase

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Area of Science:

  • Microscopy
  • Image Simulation
  • Biophysics

Background:

  • Partially coherent illumination in biological phase microscopy is difficult to simulate, limiting the use of image simulation.
  • Existing simulation methods do not fully exploit the capabilities of widely used biological phase microscopy techniques.

Purpose of the Study:

  • To introduce an open-source toolbox, microlith, for accurate 3D image prediction in biological phase microscopy.
  • To validate the accuracy of microlith by comparing simulated and experimental microscopy images.
  • To explore the application of microlith in understanding dark-field microscopy sensitivity and detecting nanoscale changes.

Main Methods:

  • Development of the open-source microlith toolbox for simulating partially coherent illumination in microscopy.
  • Comparison of simulated bright-field and dark-field images with experimental data from well-characterized targets.
  • Analysis of dark-field microscope sensitivity to mass distributions at the nanoscale.

Main Results:

  • Microlith accurately predicts 3D images for various illumination conditions (partially coherent, coherent, incoherent).
  • Experimental validation confirms the accuracy of simulated bright-field and dark-field images.
  • New insights into dark-field microscopy's sensitivity to 10nm-scale mass distributions were gained.

Conclusions:

  • The microlith toolbox enhances the application of image simulation in biological phase microscopy.
  • Dark-field microscopy shows significant sensitivity to nanoscale mass distributions.
  • A novel approach for detecting nanoscale structural changes in axonemes using dark-field microscopy is proposed.