Abstract
Three-dimensional (3D) analysis of cardiomyocytes using computers is urgently required to elucidate the pathogenesis of cardiac diseases. As there exists several different types of cells in microscopic images, it is necessary to classify the cells prior to analysis. To classify cells, the fact that the cell nuclei of vascular endothelial cells are covered by vascular endothelial cell membrane is considered. In this study, the cell nuclei and areas of the vascular endothelial cell membrane are extracted from microscopic images of myocardial tissue in the left atrium of newborn mice and classified into vascular endothelial cell nuclei and non-endothelial cell nuclei based on the quantity of the cell nuclei that is covered by the vascular endothelium. The accuracy was calculated from the experimental results, and it was more than 85%. Future studies will include improving the accuracy of the classification and further classifying the cell nuclei that were determined to be other than endothelial cell nuclei to analyze the cells. These are expected to contribute to the research to clarify the mechanism of blood vessels and cells in myocardium.
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References
Ministry of Health, Labour and Welfare, Summary of the 2020 Vital Statistics Monthly Report Annual Total (Approximate). https://www.mhlw.go.jp/toukei/saikin/hw/jinkou/geppo/nengai20/dl/gaikyouR2.pdf. Accessed 07 Dec 2021
Ministry of Education, Culture, Sports, Science and Technology (MEXT) Strategic Research on Heart Failure Elucidation of the pathogenesis of heart failure using developmental engineering and gene and cell therapy. https://www.mext.go.jp/a_menu/shinkou/hojyo/1300506.htm. Accessed 07 Dec 2021
Bao, N.P., et al.: The oxygen rich postnatal environment induces cardiomyocyte cell cycle arrest through DNA damage response. Cell 157(3), 565–579 (2014)
Nomura, S., Satoh, M., Fujita, T., et al.: Cardiomyocyte gene programs encoding morphological and functional signatures in cardiac hypertrophy and failure. Nat. Commun. 9, 4435 (2018)
Kalinin, A.A., Allyn-Feuer, A., Ade, A., et al.: 3D shape modeling for cell nuclear morphological analysis and classification. Sci. Rep. 8, 13658 (2018)
Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 234–241. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-24574-4_28
Çiçek, Ö., Abdulkadir, A., Lienkamp, S.S., Brox, T., Ronneberger, O.: 3D U-Net: learning dense volumetric segmentation from sparse annotation. In: Ourselin, S., Joskowicz, L., Sabuncu, M.R., Unal, G., Wells, W. (eds.) MICCAI 2016. LNCS, vol. 9901, pp. 424–432. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46723-8_49
Stringer, C., Wang, T., Michaelos, M., et al.: Cellpose: a generalist algorithm for cellular segmentation. Nat. Methods 18, 100–106 (2021)
Takematsu, A., Migita, M., Toda, M., Arima, Y.: Study on 3D extraction and analysis of blood vessels and cardiomyocytes on neonatal murine. In: Jeong, H., Sumi, K. (eds.) IW-FCV 2021. CCIS, vol. 1405, pp. 117–130. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-81638-4_10
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Kaneko, S., Arima, Y., Migita, M., Toda, M. (2022). Proposal of a Method to Identify Vascular Endothelial Cells from Images of Mouse Myocardial Tissue. In: Sumi, K., Na, I.S., Kaneko, N. (eds) Frontiers of Computer Vision. IW-FCV 2022. Communications in Computer and Information Science, vol 1578. Springer, Cham. https://doi.org/10.1007/978-3-031-06381-7_12
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