title: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¼ÐµÑÐ¾Ð´Ð° Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ ÑÐ°Ð·Ð±Ð¸ÐµÐ½Ð¸Ñ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹ Ð¼Ð¾Ð·Ð³Ð° Ð¿Ð»Ð¾Ð´Ð¾Ð²Ð¾Ð¹ Ð¼ÑÑÐºÐ¸ Ð½Ð° Ð¾Ð±Ð»Ð°ÑÑÐ¸
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Development of a method for automatic splitting of fruit fly brain images into regions
Creators: name: ÐÑÑÐºÐ¸Ð½, ÐÐ»ÐµÐºÑÐ°Ð½Ð´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: 2021
Subjects: Ð´ÑÐ¾Ð·Ð¾ÑÐ¸Ð»Ð°
Ð¼Ð¾Ð·Ð³
ÐºÐ»Ð°ÑÑÐµÑÐ¸Ð·Ð°ÑÐ¸Ñ
Ð³ÑÐ°ÑÑ
Ð¼Ð¾Ð´ÑÐ»ÑÐ½Ð¾ÑÑÑ
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
drosophila
brain
clusterization
graphs
modularity
machine learning

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description: In this work, a method was developed for automatically splitting an image of a fruit fly brain in an area. This algorithm speeds up and simplifies the analysis of functional areas of the fruit fly brain. A comparative analysis of classical clustering algorithms, such as k-means, BIRCH and a hierarchical clustering algorithm, which works from the bottom up, combining clusters with the minimum standard deviation, with the algorithm implemented in this work, was carried out. The algorithm implemented in this work is genetic. Several types of mutations were invented and implemented: - extracting mutation - separating mutation, having two modifications: random, which randomly bisects the cluster and deterministic, which removes the edges through which the greatest number of shortest paths in a given graph passes until the graph is no longer connected - merging mutation A metric was developed by which the quality of the partitions was compared. A parallel version of the genetic algorithm was also developed, which significantly accelerated its work. An inconsistency of the classifiers from the scikit-learn package has been fixed. Numerical experiments were performed to break the brains of fruit flies for six experimental samples. The developed genetic algorithm has shown its superiority over the classical clustering algorithms.