title: ÐÐ½Ð°Ð»Ð¸Ð· ÑÐ¾ÑÐ¼Ñ 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: Dendritic spine shape analysis
Creators: name: ÐÐ°ÑÐ¸Ð»ÑÐµÐ², ÐÐµÑ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: 2022
Subjects: ÐÐ±ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹
Ð´ÐµÐ½Ð´ÑÐ¸ÑÐ½ÑÐµ ÑÐ¸Ð¿Ð¸ÐºÐ¸
ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ñ
ÐºÐ»Ð°ÑÑÐµÑÐ¸Ð·Ð°ÑÐ¸Ñ
dendritic spines
segmentation
clusterization

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description: The subject of the graduate qualification work is: "Dendritic spine shape analysis". This work is focused on examination of existing approaches to the analysis of dendritic spine morphology and development of a new method for three-dimensional shape analysis. A semi-automated algorithm for segmentation of three-dimensional confocal microscopy images was developed. Existing numerical descriptors of dendritic spine shape were examined and a descriptor that had not previously been used for this problem was introduced - chord length distribution histogram. The developed semi-automatic segmentation algorithm is based on reconstructing dendriteâs surface as a polygonal mesh and extracting a curve skeleton. Segmentation is performed using skeleton graph structure and surface-to-skeleton distance. 31 confocal microscopy images were segmented using the developed algorithm to obtain a dataset of 214 polygonal meshes of individual dendritic spines. The obtained dataset was clustered using k-means and DBSCAN algorithms. Clustering was performed separately based on previously published set of shape descriptors and introduced chord length distribution histogram descriptor. PCA-based data dimension reduction was examined.