Registration of Regeneration in Planarians from Photographic Images
DOI:
https://doi.org/10.18287/JBPE21.07.030303Keywords:
planarians, digital morphometry, medial representation, image skeletonAbstract
In this study, an approach to constructing a mathematical model for quantifying the dynamics of regeneration of planarian flatworms in biological experiments is considered, based on an analysis of a series of digital microscopic images. A method is proposed to describe the body shape of a planarian using a continuous morphological model, based on the concept of a medial representation of the worm’s silhouette. The silhouette in this case is a polygon approximating the contours of the planarian’s body. The medial representation of the figure includes a medial axis and a radial function that describes the width of the figure relative to the medial axis. We propose a set of morphological criteria for assessing the dynamics of regeneration based on a continuous morphological model and present the results of computational experiments.References
K. P. Tiras, V. I. Khachko, “Criteria and stages of regeneration in planarians,” Ontogenez 21(6), 620–624 (1990) [in Russian].
K. P. Tiras, O. N. Petrova, S. N. Myakisheva, A. A. Deyev, and K. B. Aslanidi, “Minimizing of morphometric errors in planarian regeneration,” Fundamental Research 2(7), 1412–1416 (2015) [in Russian].
S. Flygare, M. Campbell, R. M. Ross, B. Moore, and M. Yandell, “ImagePlane: an automated image analysis pipeline for high-throughput screens using the planarian Schmidtea mediterranea,” Journal of Computational Biology 20(8), 583–592 (2013).
N. Macleod, “On the Use of Machine Learning in Morphometric Analysis,” Biological Shape Analysis: Proceedings of the 4th International Symposium, World Scientific Publishing, 134–171 (2017).
L. M. Mestetskiy, K. P. Tiras, “Morphological assessment of the dynamics of regeneration of planarians from photographic images,” Mathematical Methods for Pattern Recognition 18(1), 120–121 (2017) [in Russian].
K. P. Tiras, L. M. Mestetskiy, “Normalization of planarian images by the fat curve method in biological research,” in 17th International Conference on Mathematical Methods for Pattern Recognition, Svetlogorsk, 19–25 September 2015, 182–183 (2015) [in Russian].
K. Tiras, U. Vorobeva, K. Novikov, V. Voeikov, V. Emelyanenko, G. Davidova, and A. Skripnikov, “Peptide regulation of plant and animal morphogenesis: general mechanisms and specificity of action,” IOP Conference Series: Materials Science and Engineering 487, 012020 (2019).
L. M. Mestetskiy, Continuous morphology of binary images: figures, skeletons, circulars, Moscow, Fizmatlit (2009) [in Russian]. ISBN: 978-5-9221-1050-1.
R. Gonzalez, R. Woods, Digital Image Processing, 4th ed., Pearson, India (2018).
X. Wang, M. G. Mitchum, B. Gao, C. Li, H. Diab, T. J. Baum, R. S. Hussey, and E. L. Davis, “A parasitism gene from a plant-parasitic nematode with function similar to CLAVATA3/ESR (CLE) of Arabidopsis thaliana,” Molecular Plant Pathology 6(2), 187–191 (2005).
V. P. Sherendak, I. A. Bratchenko, O. O. Myakinin, P. N. Volkhin, Y. A. Khristoforova, A. A. Moryatov, A. S. Machikhin, V. E. Pozhar, S. G. Kozlov, and V. P. Zakharov, “Hyperspectral in vivo analysis of normal skin chromophores and visualization of oncological pathologies,” Computer Optics 43(4), 661–670 (2019).
L. Bratchenko, I. Bratchenko, Y. Khristoforova, D. Artemyev, Y. Konovalova, P. Lebedev, and V. Zakharov, “Raman spectroscopy of human skin for kidney failure detection,” Journal of Biophotonics 14(6), e202000360 (2020).
Downloads
Published
Issue
Section
License
Copyright (c) 2021 Kharlampiy Tiras, Leonid Mestetsky, Svetlana Nefedova, Nikita Lomov

This work is licensed under a Creative Commons Attribution 4.0 International License.
Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.













