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Updated: Feb 28, 2026

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning
Published on: November 19, 2018
New quantitative features for the morphological differentiation of abnormal lymphoid cell images from peripheral
Laura Puigví1,2, Anna Merino1, Santiago Alférez2
1Biomedical Diagnostic Center, Hospital Clínic of Barcelona, University of Barcelona, Barcelona, Spain.
Aims:
This work aims to propose a set of quantitative features through digital image analysis for significant morphological qualitative features of different cells for an objective discrimination among reactive, abnormal and blast lymphoid cells.
Methods:
Abnormal lymphoid cells circulating in peripheral blood in chronic lymphocytic leukaemia, B-prolymphocytic leukaemia, hairy cell leukaemia, splenic marginal zone lymphoma, mantle cell lymphoma, follicular lymphoma, T-prolymphocytic leukaemia, T large granular lymphocytic leukaemia and Sézary syndrome, normal, reactive and blast lymphoid cells were included. From 325 patients, 12 574 cell images were obtained and 2676 features (27 geometric and 2649 related to colour and texture) were extracted and analysed.
Results:
We analysed the 20 most relevant features for the morphological differentiation of the 12 lymphoid cell groups under study. Most of them showed significant differences: 19 comparing follicular and mantle cells, 18 for blast and reactive cells, 17 for Sézary cells and T prolymphocytes and 16 for B and T prolymphocytes and 16 for villous lymphocytes. Moreover, a total of five quantitative features were significant for the discrimination among reactive and the set of abnormal lymphoid cells included.
Conclusions:
Image analysis may assist in quantifying cell morphology turning qualitative data into quantitative values. New cytological variables were established based on geometric and colour/texture features to contribute to a more accurate and objective morphological assessment of lymphoid cells and their association with flow cytometry methods may be interesting to explore in the next future.
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