Abstract
The cell morphology analysis is applicable to pathophysiology studies in biological samples. In this work, digital images of Human Umbilical Vascular Endothelial Cells (HUVEC) were classified according to their morphological properties, to help the detection of functional and/or structural anomalies for the study of angiogenesis, a process by which new capillaries are formed from pre-existing capillaries. The automatic classification was produced by the algorithms: support vector machine (SVM), k-Nearest Neighbors (k-NN), and decision trees (DT), with three classes: circular, elongated deformed (elongated), and slightly elongated deformed (others deformations). The processes of cell migration and proliferation could be correlated with this classification. The sensitivity values for all three methods exceed 95%. The highest accuracy value, 98.89%, was reached by SVM method. Results shows that it is feasible to use these three methods for the classification of HUVEC.
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Acknowledgment
This work was supported by the Brazilian research agencies CAPES, FAPESP, and CNPq through their project PDJ 402601/2015-7, the University of Sao Paulo and Fluminense University, both in Brazil, and the Universidad de Oriente, Cuba. To Professors Durvanei Augusto Maria of the Bu-tantan Institute, Dr. C. Mikiya Muramatsu, Dr. C. Adriano Alencar, and Dr. C. Diogo Soga of the Institute of Physics of the University of Sao Paulo, Brazil. To Project PT241SC003-006 of the Territorial Program CITMA Santiago Delegation for Development of Health Products and Services 2020.
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Escobedo-Nicot, M., Delgado-Font, W., Monteiro-Pereira, E., Ferreira-Gomes, L. (2024). Automatic Morphological Evaluation of Endothelial Cells Using Different Classification Methods. In: Marques, J.L.B., Rodrigues, C.R., Suzuki, D.O.H., Marino Neto, J., García Ojeda, R. (eds) IX Latin American Congress on Biomedical Engineering and XXVIII Brazilian Congress on Biomedical Engineering. CLAIB CBEB 2022 2022. IFMBE Proceedings, vol 99. Springer, Cham. https://doi.org/10.1007/978-3-031-49404-8_56
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