Abstract
The combination of a fractal formalism with linear methods of image analysis is the basis of a statistically reliable description of the morphology and classification of forms that are irregular from the point of view of Euclidean geometry, such as in vitro flattened amoeboid cells. We have developed a classification algorithm that is based on the morphological characteristics of immune cells of four species of marine invertebrates: the bivalves Spisula sachalinensis (Schrenck, 1862) and Callista brevisiphonata (Carpenter, 1864) and the echinoderms Aphelasterias japonica (Bell, 1881) and Asterias amurensis (Lutken, 1871). The morphological signs of the cells included dimensional characteristics (area and perimeter), features of the circle and the convex hull that circumscribes the cell, characteristics of the symmetry and roundness of the cell, as well as fractal dimension and lacunarity, which were determined in several ways while assessing the spatial complexity of cells. It was shown that the optimal classification structure of immune cells of all studied species is based on a similar universal algorithm, including hierarchical classification by the Ward method, using variables with the highest multimodality index that load different factors in the factor analysis.
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