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A high-throughput imaging and quantification pipeline for the EVOS imaging platform.

Stefan Donovan Klimaj1, Yamhilette Licon Munoz1, Katelyn Del Toro1

  • 1Department of Biochemistry and Molecular Biology, University of New Mexico School of Medicine, Albuquerque, New Mexico, United States of America.

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Automated cell counting from tiled images is challenging due to artifacts. This study developed a robust pipeline to overcome these issues, enabling accurate cell quantification for high-throughput applications.

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Area of Science:

  • Cell Biology
  • Microscopy
  • Bioimaging

Background:

  • Self-contained imaging systems with motorized stages and incubators are essential for live-cell imaging and high-throughput applications.
  • The EVOS imaging system can scan multi-well dishes and stitch fields for well imaging, but automated analysis of these tiled images presents challenges.
  • Initial attempts at quantifying tiled images faced issues like high background, artifacts, low contrast, noise, and distortion, hindering processing efficiency.

Purpose of the Study:

  • To develop and optimize an automated image analysis pipeline for accurate cell counting from tiled images generated by the EVOS imaging system.
  • To address and overcome common image processing challenges encountered with automated batch analysis of tiled microscopy data.

Main Methods:

  • Development of a rigorous cell counting pipeline tailored for tiled images from the EVOS scan function.
  • Optimization of image processing steps to mitigate artifacts such as high background, illumination and stitching issues, low contrast, noise, focus inconsistencies, and image distortion.

Main Results:

  • Successfully overcame expected and unforeseen obstacles in automated tiled image analysis.
  • Created a robust and facile automated pipeline for accurate cell counting.
  • Demonstrated the pipeline's effectiveness in handling complex image artifacts.

Conclusions:

  • The developed automated pipeline provides an effective solution for accurate cell counting from EVOS-generated tiled images.
  • This tool facilitates high-throughput analysis of live-cell imaging data, overcoming previous processing limitations.
  • The pipeline represents a significant advancement for cell culture laboratories utilizing automated imaging systems.