Abstract
Using rubricytes and lymphocytes as examples, this paper presents a fuzzy set theory and method to identify human bone marrow hematopoiesis system cells (BMCs). On the basis of the Cauchy’s distribution function, this paper sets up a series of membership function formulae of the BMC feature fuzzy subsets, general identification formulae of fuzzy sets for the BMCs, as well as identification formulae of fuzzy sets for rubricytes and lymphocytes. These formulae will assist with the quantitation of unknown cells compared to standard cells.
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References
Bacus J. W. and Gose E. E., Leukocyte pattern recognition, IEEE Transactions on System, Man and Cybernetics, 1972, SMC-2:513–526
Beksac M., Beksac M. S., Tipi V. B., et al., An artificial intelligent diagnostic system on differential recognition of hematopoietic cells from microscopic images, Cytometry, 1997, 30:145–150
Bins M., Landeweerd G. H., Gelsema E. S., et al., Texture of white blood cells expressed by the counting densitogram, Cytometry, 1981, 1:321–324
Brenner J. F., Gelsema E. S., Necheles T. F., et al., Automated classification of normal and abnormal leukocytes, The Journal of Histochemistry and Cytochemistry, 1974, 22:697–706
Brown B. A., Hematology: Principles and Procedures, 6th ed., Philadelphia, Lea & Febiger, 1993:13–15, 39–41, 77–78
Garthwaite P. H., Jolliffe I. T. and Jones B., Statistical Inference, London, Prentice Hall International Limited, 1995:10
Gauvain C., Seigneurin D. and Brugal G., A Quantitative analysis of the human bone marrow erythroblastic cell lineage using the SAMBA 200 cell image processor, I The normal maturation sequence, Analytical and Quantitative Cytology and Histology, 1987, 9:253–262
Harmening D. M., Clinical Hematology and Fundamentals of Homeostasis, 2nd ed., Philadelphia, F. A. Davis Company, 1992:28–39,44
Harms H., Gunzer U., Aus H. M., et al., Computer aided analysis of chromatin network and basophil color for differentiation of mononuclear peripheral blood cells, The Journal of Histochemistry and Cytochemistry, 1979, 27:204–209
Harms H., Gunzer U., Baumann I., et al., Malignancy-associated changes in monocytes and lymphocytes in acute leukemias measured by high-resolution image processing, Analytical and Quantitative Cytology and Histology, 1993, 15:371–378
Miale J. B., Laboratory Medicine: Hematology, St. Louis, The C. V. Mosby Co., 1982:122,137–142
Mui J. K., Fu K. S. and Bacus J. W., Automated classification of blood cell neutrophils, The Journal of Histochemistry and Cytochemistry, 1977, 25:633–640
Pogorelov V. M., Timkina E. N., Mattes G., et al., The monitoring of acute leukemia patients: Part 1. Basic morphometric characteristics of bone marrow blast cells in acute lymphoblastic leukemia, Leukemia Research, 1990, 14: 795–800
Qian M. P. and Chen C. J., Carcinoma cell identification by fuzzy method, Progress of Biochemistry and Biophysics, 1979, 3:66–71 (in Chinese)
Seigneurin D., Gauvain C. and Brugal G., A Quantitative analysis of the human bone marrow granulocytic cell lineage using the SAMBA 200 cell image processor, I The normal maturation sequences, Analytical and Quantitative Cytology and Histology, 1984, 6:168–178
Vastola E. F., Hertzberg R., Neurath P., et al., A description by computer of texture in wright-stained leukocytes, Acta Cytologica, 1974, 18:231–247
Young I. T., The classification of white blood cells, IEEE Transactions on Biomedical Engineering, 1972, BME-19:291–298
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Wang, R., Nuttall, K.L., Fenn, J.P. et al. Fuzzy set identification of bone marrow cells. J. of Shanghai Univ. 3, 70–73 (1999). https://doi.org/10.1007/s11741-999-0033-4
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DOI: https://doi.org/10.1007/s11741-999-0033-4