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Updated: May 3, 2026

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning
Published on: November 19, 2018
Morphometry to identify subtypes of leukocytes
Pablo B Tozetti1, Ewelyne M Lima1, Andrews M Nascimento1
1Master's Program in Pharmaceutical Sciences, University of Vila Velha (UVV), Vila Velha, ES, Brazil.
Introduction:
Recent studies in image cytometry evaluated the replacement of specific markers by morphological parameters. The aim of this study was to develop and evaluate a method to identify subtypes of leukocytes using morphometric data of the nuclei.
Method:
The analyzed images were generated with a laser scanning cytometer. Two free programs were used for image analysis and statistical evaluation: Cellprofiler and Tanagra respectively. A sample of leukocytes with 200 sets of images (DAPI, CD45 and CD14) was analyzed. Using feature selection, the 20 best parameters were chosen to conduct cross-validation.
Results:
The morphometric data identified the subpopulations of the analyzed leukocytes with a sensitivity and specificity of 0.95 per sample.
Conclusion:
The present study is the first that identifies subpopulations of leukocytes by nuclear morphology.
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