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Efficient Double Helix Detection with Steerable Filters.

Andrew E S Barentine1, Ashwin Balaji1,2, W E Moerner1

  • 1Department of Chemistry, Stanford University, Stanford, California 94305, USA.

Biorxiv : the Preprint Server for Biology
|September 2, 2025
PubMed
Summary
This summary is machine-generated.

We developed a fast method to find Double Helix point-spread functions for 3D microscopy. This technique efficiently estimates 2D position and axial position, significantly reducing computational cost for single-molecule localization microscopy.

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Area of Science:

  • Biophysics
  • Optical Microscopy
  • Computational Imaging

Background:

  • Accurate 3D single-molecule localization microscopy (SMLM) is crucial for understanding molecular behavior.
  • Localization precision is often limited by the accuracy of point-spread function (PSF) detection and fitting.
  • Existing deep learning methods for PSF analysis can be computationally intensive.

Purpose of the Study:

  • To present an efficient detection scheme for localizing Double Helix point-spread functions (PSFs) in 3D SMLM.
  • To develop a computationally inexpensive yet accurate method for determining both lateral and axial positions of single molecules.
  • To integrate this scheme into a complete SMLM analysis pipeline.

Main Methods:

  • Utilized steerable filters for rapid extraction of 2D position and lobe orientation (axial position) from Double Helix PSFs.
  • Employed a double Gaussian model fitter with optimal parameterization for enhanced localization accuracy.
  • Implemented the detection and fitting scheme as a plugin for the open-source PYthon Microscopy Environment (PYME).

Main Results:

  • Achieved efficient localization using only 7 convolutions, a significant reduction compared to deep learning approaches.
  • Demonstrated accurate estimation of both 2D position and axial position from Double Helix PSFs.
  • Successfully integrated the method into a functional SMLM analysis pipeline within PYME.

Conclusions:

  • The proposed steerable filter-based detection scheme offers a computationally efficient alternative for 3D SMLM.
  • This method provides accurate localization of Double Helix PSFs, improving SMLM analysis.
  • The PYME plugin facilitates the adoption of this advanced technique in biological research.