title: ÐÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ ÐºÐ¾Ð¼Ð¿Ð»ÐµÐºÑÐ½ÑÑ Ð´ÐµÑÐºÑÐ¸Ð¿ÑÐ¾ÑÐ¾Ð² ÑÐ¾ÑÐ¼Ñ Ð´Ð»Ñ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð¼Ð¾ÑÑÐ¾Ð»Ð¾Ð³Ð¸Ð¸ Ð´ÐµÐ½Ð´ÑÐ¸ÑÐ½ÑÑ ÑÐ¸Ð¿Ð¸ÐºÐ¾Ð²
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Using complex shape descriptors to analysis of the morphology of dendritic spines
Creators: name: Ð¡Ð¼Ð¸ÑÐ½Ð¾Ð²Ð°, ÐÐ°ÑÑÑ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: ÐÐ°ÑÐµÐ¼Ð°ÑÐ¸ÐºÐ°
ÐÐ½ÑÐ¾ÑÐ¼Ð°ÑÐ¸ÐºÐ°
Ð¼Ð¾ÑÑÐ¾Ð»Ð¾Ð³Ð¸Ñ Ð´ÐµÐ½Ð´ÑÐ¸ÑÐ½ÑÑ ÑÐ¸Ð¿Ð¸ÐºÐ¾Ð²
Ð´ÐµÑÐºÑÐ¸Ð¿ÑÐ¾ÑÑ ÑÐ¾ÑÐ¼Ñ
ÐºÐ»Ð°ÑÑÐµÑÐ¸Ð·Ð°ÑÐ¸Ñ
ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ
dendritic spines morphology
shape descriptors
clustering
classification

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description: The subject of the graduate qualification work is Â«Title of the thesisÂ». This work is dedicated to the study of existing methods for analyzing the morphological features of dendritic spines and the development of new shape descriptors based on orthogonal decompositions: spherical harmonics and Zernike moments, which were previously used to describe the shape of engineering objects. The study explores the application of these orthogonal decompositions to the analysis of dendritic spines and develops a method for calculating the descriptors. An analysis of these features was conducted on a dataset of dendrites from mouse neurons of various groups, including neurons modeling Alzheimerâs disease. For the analysis, 1256 dendritic spines were extracted from microscopic images using the SpineTool software. The dataset included four groups of dendrites: wild-type (Wt) mice, Ab-type mice, and dendrites from these groups of mice exposed to a substance that stimulates synaptic improvement. Morphological features based on spherical harmonics and Zernike moments were calculated for the dataset, along with previously described features such as the histogram of chord lengths and 11 classical scalar indicators like length, volume, and others. Experiments demonstrated that the proposed shape descriptors show high efficiency in the tasks of classification and cluster analysis of dendritic spine morphology. The new descriptors outperformed traditional shape metrics in classifying neurons of healthy and Alzheimerâs disease mice. The use of spherical harmonics and Zernike moments improved the quality of cluster analysis, revealing more distinct and significant data groups.