Abstract
Developing computational analysis of time-lapse imaging of calcium events in astrocytes is a challenging task in neuroscience. Here we report the implementation of an algorithm that solves this task. After noise reduction with the block-matching and 3D filtering (BM3D) algorithm, calcium activity is identified as fluorescence elevation above the baseline level. Individual events are detected by sliding window approach applied to the variation of pixel intensity relative to the baseline level. The maximal projection and duration of astrocytic calcium events are then assessed. The novelty of the proposed method is an adaptive construction of the baseline level. The statistical results generated by our program are consistent with the previous algorithm reported and used by us for the reference. The software is publicly available.
This research financially supported by Russian Science Foundation (AZ to 16-12-00077, algorithm; AS to 16-14-00201, data analysis).
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Kustikova, V. et al. (2018). CalciumCV: Computer Vision Software for Calcium Signaling in Astrocytes. In: van der Aalst, W., et al. Analysis of Images, Social Networks and Texts. AIST 2018. Lecture Notes in Computer Science(), vol 11179. Springer, Cham. https://doi.org/10.1007/978-3-030-11027-7_17
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