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Comparison between two programs for image analysis, machine learning and subsequent classification.

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Summary
This summary is machine-generated.

This study compared CellProfiler and QuPath for image analysis and machine learning classification. Both software programs showed comparable results, with QuPath offering a more user-friendly experience for renal tissue analysis.

Keywords:
Cellular diagnosisImage cytometryMachine learning

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Area of Science:

  • Digital Pathology
  • Computational Biology
  • Biomedical Imaging

Background:

  • Automated quantitative cellular analysis began with flow cytometry in the 1950s.
  • Image cytometry, specifically laser scanning cytometry (LSC), emerged in the early 1990s, offering comparable results to flow cytometry.
  • Image analysis software like ImageJ, CellProfiler, CellProfiler Analyst, and QuPath have advanced morphological and diagnostic capabilities.

Purpose of the Study:

  • To compare the performance of two free image analysis software programs, CellProfiler and QuPath.
  • To evaluate their effectiveness in subsequent machine learning-based classification.
  • To assess their utility for analyzing renal tissue images.

Main Methods:

  • Analysis of renal tissue images stained with HIF and TUNEL.
  • Loading identical images into both CellProfiler and QuPath for processing.
  • Utilizing advanced statistical analysis, including the Bland-Altman assay, to compare results.
  • Employing machine learning for classification of identified objects.

Main Results:

  • The Bland-Altman assay indicated that the differences between CellProfiler and QuPath were normally distributed and within acceptable limits, demonstrating comparability.
  • QuPath was found to be easier to use for the analyzed renal tissue samples.
  • QuPath facilitated image analysis without requiring prior image pre-processing steps and allowed for unsupervised machine learning.

Conclusions:

  • CellProfiler and QuPath are comparable free software programs for image analysis and machine learning classification.
  • QuPath offers a more streamlined and user-friendly workflow, particularly for complex biological samples like renal tissue.
  • The choice of software may depend on specific experimental needs and user preference for pre-processing and machine learning approaches.