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Computer automated cell size and shape analysis in cryomicroscopy.

K R Diller, S J Aggarwal

    Journal of Microscopy
    |May 1, 1987
    PubMed
    Summary
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    Computer vision quantifies cell size and shape changes during cryomicroscopy. Differential interference contrast microscopy provided the most consistent data, outperforming bright field and phase contrast imaging for accurate analysis.

    Area of Science:

    • Cell biology
    • Image analysis
    • Biophysics

    Background:

    • Quantitative analysis of cellular changes during cryopreservation is crucial.
    • Computer vision offers automated methods for analyzing cell morphology.
    • Cryomicroscopy presents challenges due to ice crystal formation and optical distortions.

    Purpose of the Study:

    • To evaluate the sensitivity of computer vision-based cell analysis.
    • To compare different microscopy optical systems for cryomicroscopy image analysis.
    • To assess the impact of image defocusing on quantitative cell measurements.

    Main Methods:

    • Standard serial edge detection algorithms and shape transforms were implemented.
    • Automated analysis was tested on images from bright field, differential interference contrast (DIC), and phase contrast microscopy.

    Related Experiment Videos

  • Calibration trials used latex spheres with extracellular ice; pancreas beta-cells were analyzed as an example.

    • Main Results:

    • Differential interference contrast (DIC) microscopy yielded the most consistent size measurements.
    • Bright field microscopy showed less sensitivity to extracellular ice.
    • Phase contrast microscopy produced the least accurate quantitative data.

    Conclusions:

    • The sensitivity of automated computer vision analysis varies with microscopy technique.
    • DIC microscopy is recommended for accurate quantitative analysis of cells in cryomicroscopy.
    • Image quality and optical system choice significantly impact the reliability of cell size and shape analysis.