Computational Methods for Neuron Segmentation in Two-Photon Calcium Imaging Data: A Survey
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Published:2022-07-07
Issue:14
Volume:12
Page:6876
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ISSN:2076-3417
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Container-title:Applied Sciences
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language:en
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Short-container-title:Applied Sciences
Author:
Abbas WaseemORCID,
Masip DavidORCID
Abstract
Calcium imaging has rapidly become a methodology of choice for real-time in vivo neuron analysis. Its application to large sets of data requires automated tools to annotate and segment cells, allowing scalable image segmentation under reproducible criteria. In this paper, we review and summarize the most recent methods for computational segmentation of calcium imaging. The contributions of the paper are three-fold: we provide an overview of the main algorithms taxonomized in three categories (signal processing, matrix factorization and machine learning-based approaches), we highlight the main advantages and disadvantages of each category and we provide a summary of the performance of the methods that have been tested on public benchmarks (with links to the public code when available).
Funder
Spanish Ministry of Science, Innovation and Universities
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
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