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Creating and troubleshooting microscopy analysis workflows: Common challenges and common solutions.

Beth A Cimini
Published in: Journal of microscopy (2024)
As microscopy diversifies and becomes ever more complex, the problem of quantification of microscopy images has emerged as a major roadblock for many researchers. All researchers must face certain challenges in turning microscopy images into answers, independent of their scientific question and the images they have generated. Challenges may arise at many stages throughout the analysis process, including handling of the image files, image pre-processing, object finding, or measurement, and statistical analysis. While the exact solution required for each obstacle will be problem-specific, by keeping analysis in mind, optimizing data quality, understanding tools and tradeoffs, breaking workflows and data sets into chunks, talking to experts, and thoroughly documenting what has been done, analysts at any experience level can learn to overcome these challenges and create better and easier image analyses.
Keyphrases
  • deep learning
  • optical coherence tomography
  • single molecule
  • high resolution
  • high throughput
  • convolutional neural network
  • machine learning
  • big data
  • label free
  • artificial intelligence