Image processing and analysis in lung cancer cells growth

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Abstract

Modern diagnostic methods allow to get multiple information regarding research material. Patients diagnosis is performed using highly specialized tools, effectively supporting any medical diagnostic processes. This paper focuses on the analysis of lung cancer cell cultures growth and migration in vitro. Most of the publications on the growth rate of cells is based on the analysis of changes in surface area, less wide cracks. This study determined there are additional parameters like cells angle, number of cells and distance between cells, with separate cells up and down the scratch in all parameters, that affect how the migration of cells which have not been considered previously. Analysis on the arrangement of the cells and the distances between them, allow for determination of the level of cell migration. Experience has shown that on the first day a high proliferation of cells, and then clear their migration, increasing the distance. It was also noted changing the angle of the cells that begin migration. The performed analysis confirmed that those additional parameters differentiate correctly evaluated a group of images. Developed algorithm of image processing and analysis, operates on data from a collection of microscopic images of lung cancer cells in vitro propagation, acquiring data on the growth and migration of cancer cells. As a result the data contain a description of parameters studied images in the form of growth profiles over time and the type of growth.

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Jedrusik, P., Walusiak, Ł., Bednarek, I., Koprowski, R., & Wróbel, Z. (2018). Image processing and analysis in lung cancer cells growth. In Advances in Intelligent Systems and Computing (Vol. 578, pp. 346–356). Springer Verlag. https://doi.org/10.1007/978-3-319-59162-9_36

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