Abstract
The article deals with the design of a method for the automatic detection of static objects in the image captured by an optical microscope. The search algorithm for static objects in the image - non-moving cilia is based on texture description methods. The texture of the image is described by statistical values, where it can be noticed that background texture, cells and cilia have different mathematical statistical parameters. Just based on the different statistical parameters of the textures, the classification for each texture parameter was done separately. As a result, the resulting classification considers the most predominant group to which the pixel has been assigned. In the end, the obtained mask was adjusted by morphological operations to obtain the boundary of the area, where the algorithm automatically evaluated that one was about Cilia. 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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Acknowledgment
Authors of this paper wish to kindly thank all supporting bodies, especially to grant APVV-15-0462: Research on sophisticated methods for analyzing the dynamic properties of respiratory epithelium’s microscopic elements.
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Jabloncik, F., Hargas, L., Volak, J., Koniar, D. (2019). Detection of Static Objects in an Image Based on Texture Analysis. 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_40
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DOI: https://doi.org/10.1007/978-3-030-17935-9_40
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