Open AccessK-means clustering of zebrafish embryos images acquired with AOTF-based hyperspectral microscope
Author(s) -
A. V. Burlakov,
S V Shirokov,
Chih Chung Huang,
Demid D. Khokhlov
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2127/1/012062
Subject(s) - hyperspectral imaging , zebrafish , microscope , computer science , artificial intelligence , cluster analysis , computer vision , perspective (graphical) , modality (human–computer interaction) , filter (signal processing) , biology , optics , physics , biochemistry , gene
Model organism studies are widely implemented in biomedical research fields. Zebrafish is a common and convenient model organism. To provide in vivo investigation of living zebrafish the non-invasive imaging methods are implemented. Hyperspectral imaging utilizing acousto-optic tunable filters is a perspective modality for zebrafish embryos and larvae automated observation. In this paper, the hyperspectral microscope based on the acousto-optical tunable filter is described. Using the hyperspectral image arrays obtained with the described setup, the K -means clustering algorithm is tested. The results obtained for different number of clusters are presented and discussed.