Automatically obtaining by methods of flow cytometry and cluster analysis simplified leukocyte formula
DOI:
https://doi.org/10.21638/11701/spbu10.2023.404Abstract
The leukocyte formula is the percentage of different groups of white blood cells. According to morphological features, three subpopulations can be distinguished among leukocytes: lymphocytes, monocytes and granulocytes. Granulocytes are divided into neutrophilic, eosinophilic, and basophilic cells. Automatic typologization of white blood cells is an unsolved problem, since at present, during cytometric research, the counting of the number of cells in various subpopulations of leukocytes is actually done manually, which in turn causes the subjectivity of the experiment and large values of errors in calculations. To solve this problem, attempts have been made repeatedly to use cluster analysis methods. In computational experiments, it was shown that the use of standard algorithms, such as the agglomerative methods, EM algorithm, DBSCAN, etc., does not allow to obtain the desired results. In recent years, a large number of research papers have been published describing specialized clustering algorithms for detecting and determining populations of white blood cells, some of them have found practical application, but the problems associated with the presence of a large amount of noise and different data density distribution during leukocyte clustering by flow cytometry methods remain relevant. The article considers an approach to constructing a strategy for automatic allocation of the main leukocyte subpopulations using a modified agglomerative centroid clustering method and discusses the results of computational experiments. The results of calculating the proportion of lymphocytes are compared “manually” and automatically using a modified centroid algorithm.
Keywords:
leukocyte formula, flow cytometry, cluster analysis, Markov moment, least squares method
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