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Updated: Aug 25, 2026

Using Computer Vision Libraries to Streamline Nuclei Quantification
Published on: June 6, 2025
Effects of lossy image compression on quantitative image analysis of cell nuclei
Koray Atalağ1, Murat Sincan, Bülent Celasun
1Department of Medical Education and Informatics, Faculty of Medicine, Hacettepe University, Department of Pathology, Faculty of Medicine, Gulhane Military Medical Academy, Ankara, Turkey.
Objective:
To investigate whether statistically significant changes occur in quantitative image analysis of cell nuclei when lossy image compression techniques are used.
Study Design:
Thirty-five stoichiometric, Feulgen-stained samples of rat hepatocytes, human thyroid and ovarian cancer cell nuclei were used. Image analysis was performed by a computerized system that used AutoCyte LINK V1.1.1.56 software (Burlington, North Carolina, U.S.A.) for image acquisition and Zeiss Vision KS 400 V3.0 software (Oberkochen, Germany) for quantitative image analysis. After lossy JPEG compression of acquired images at different quality levels, some densitometric features were selected and measurements performed.
Results:
We observed that nearly all the standard densitometric features showed statistically significant changes when images were compressed with the lossy JPEG algorithm. However, most invariant densitometric moment features remained free of statistically significant changes.
Conclusion:
The standard densitometric measurements that we used do not tolerate lossy compression. However, analyses using invariant densitometric features may be performed on images compressed with lossy JPEG, resulting in simpler, less expensive systems demanding less network bandwidth.
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