Authors:
Nikita Lomov
1
;
Kharlampiy Tiras
2
;
3
and
Leonid Mestetskiy
1
;
4
Affiliations:
1
Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Moscow, Russia
;
2
Institute of Theoretical and Experimental Biophysics of the Russian Academy of Sciences, Pushchino, Russia
;
3
Pushchino State Institute of Natural Science, Pushchino, Russia
;
4
Lomonosov Moscow State University, Moscow, Russia
Keyword(s):
Animal Identification, Planarian Flatworms, Skeleton, Fat Curve, Point Registration, Assignment Problem.
Abstract:
Planarian flatworms are known for their abilities to regenerate and are a popular biological model. Identification of individual planarian individuals is useful for automating biological research and improving the accuracy of measurements in experiments. The article proposes a method for identifying planaria by their texture profile, characterized by a set, shape, and position of light spots on the worm’s body— areas without pigment. To make the comparison of planaria of different sizes and in different poses, the method of planarian texture normalization is suggested. It is based on the selection of a main branch in the skeleton of a segmented image and allows one to switch to a unified coordinate system. Also, a method for creating a generalized textural profile of a planarian, based on averaging sets of spots for multiple images, is proposed. Experiments were carried out to identify planaria for different types of observations—during one day, during several days and during several
days of regeneration after decapitation. Experiments show that light spots are a temporally stable phenotypic trait.
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