Abstract
The ciliary respiratory epithelium analysis is performed to detect of possible malfunction of cilia. The moving cilia is investigated and their movement is automatically evaluated. The areas with moving cilia is marked in video sequences. When the moving cilia is searched in some cases the false detection can be occur. It means that area with no cilia is marked as ciliated epithelium. These errors are caused by artefacts. The most frequent artefacts are erythrocytes and air bubbles. Article deals with techniques that helps to find artefacts which are responsible for false detection of movement. The used techniques for artefacts detection are based on pattern matching and geometrical matching. The results of designed algorithms are compared in the conclusion of this article. The main idea of this work is to create complex diagnostic tool for evaluation of ciliated epithelium in airways. This work is supported by medical specialists from Jessenius Faculty of Medicine in Martin (Slovakia) and proposed tools would fill the gap in the diagnostics in the field of respirology in Slovakia.
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Authors of this paper wish to kindly thank to all supporting bodies, especially to grant APVV-15-0462: Research on sophisticated methods for analysing the dynamic properties of respiratory epithelium’s microscopic elements.
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Hargas, L., Loncova, Z., Koniar, D., Jabloncik, F., Volak, J. (2019). Artefacts Recognition and Elimination in Video Sequences with Ciliary Respiratory Epithelium. In: Rojas, I., Valenzuela, O., Rojas, F., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2019. Lecture Notes in Computer Science(), vol 11466. Springer, Cham. https://doi.org/10.1007/978-3-030-17935-9_41
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