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Automated Nanoparticle Analysis in Surface Plasmon Resonance Microscopy.

Xu Wang1, Qiang Zeng2, Feng Xie2

  • 1College of Automation, Hangzhou Dianzi University, Hangzhou, Zhejiang Province 310018, People's Republic of China.

Analytical Chemistry
|May 11, 2021
PubMed
Summary

This study introduces a deep learning-powered software for surface plasmon resonance microscopy (SPRM) nanoparticle analysis. The tool automates identification, counting, and motion tracking, significantly speeding up data processing for high-throughput screening.

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Area of Science:

  • Nanotechnology
  • Microscopy
  • Biophysics

Background:

  • Surface Plasmon Resonance Microscopy (SPRM) enables sensitive single nanoparticle analysis.
  • Statistical analysis of numerous nanoparticles in SPRM is labor-intensive and time-consuming.
  • Existing methods hinder high-throughput screening applications.

Purpose of the Study:

  • To develop an automated image processing software for nanoparticle analysis in SPRM.
  • To enhance the efficiency and throughput of SPRM data analysis.
  • To facilitate the translation of SPRM into digital sensing platforms.

Main Methods:

  • Development of a deep learning algorithm for image processing.
  • Implementation of automated nanoparticle identification and digital counting.
  • Integration of 3D tracking for particle location, dwell time, and Brownian motion quantification.
  • Inclusion of image filtering to enhance contrast for low refractive index nanoparticles.

Main Results:

  • Fully automated nanoparticle identification, counting, and 3D tracking achieved.
  • Quantification of dwell time and Brownian motion properties demonstrated.
  • Robust analysis of low refractive index nanoparticles from SPRM images.
  • Significant reduction in the time and labor required for statistical analysis.

Conclusions:

  • The developed software package automates critical aspects of SPRM nanoparticle analysis.
  • This tool significantly improves efficiency and enables high-throughput screening.
  • The software promotes the wider adoption of SPRM in digital sensing applications.