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Neuron tracing from light microscopy images: automation, deep learning and bench testing
MOTIVATION: Large-scale neuronal morphologies are essential to neuronal typing, connectivity characterization and brain modeling. It is widely accepted that automation is critical to the production of neuronal morphology. Despite previous survey papers about neuron tracing from light microscopy data...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9750132/ https://www.ncbi.nlm.nih.gov/pubmed/36303315 http://dx.doi.org/10.1093/bioinformatics/btac712 |
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author | Liu, Yufeng Wang, Gaoyu Ascoli, Giorgio A Zhou, Jiangning Liu, Lijuan |
author_facet | Liu, Yufeng Wang, Gaoyu Ascoli, Giorgio A Zhou, Jiangning Liu, Lijuan |
author_sort | Liu, Yufeng |
collection | PubMed |
description | MOTIVATION: Large-scale neuronal morphologies are essential to neuronal typing, connectivity characterization and brain modeling. It is widely accepted that automation is critical to the production of neuronal morphology. Despite previous survey papers about neuron tracing from light microscopy data in the last decade, thanks to the rapid development of the field, there is a need to update recent progress in a review focusing on new methods and remarkable applications. RESULTS: This review outlines neuron tracing in various scenarios with the goal to help the community understand and navigate tools and resources. We describe the status, examples and accessibility of automatic neuron tracing. We survey recent advances of the increasingly popular deep-learning enhanced methods. We highlight the semi-automatic methods for single neuron tracing of mammalian whole brains as well as the resulting datasets, each containing thousands of full neuron morphologies. Finally, we exemplify the commonly used datasets and metrics for neuron tracing bench testing. |
format | Online Article Text |
id | pubmed-9750132 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-97501322022-12-15 Neuron tracing from light microscopy images: automation, deep learning and bench testing Liu, Yufeng Wang, Gaoyu Ascoli, Giorgio A Zhou, Jiangning Liu, Lijuan Bioinformatics Review MOTIVATION: Large-scale neuronal morphologies are essential to neuronal typing, connectivity characterization and brain modeling. It is widely accepted that automation is critical to the production of neuronal morphology. Despite previous survey papers about neuron tracing from light microscopy data in the last decade, thanks to the rapid development of the field, there is a need to update recent progress in a review focusing on new methods and remarkable applications. RESULTS: This review outlines neuron tracing in various scenarios with the goal to help the community understand and navigate tools and resources. We describe the status, examples and accessibility of automatic neuron tracing. We survey recent advances of the increasingly popular deep-learning enhanced methods. We highlight the semi-automatic methods for single neuron tracing of mammalian whole brains as well as the resulting datasets, each containing thousands of full neuron morphologies. Finally, we exemplify the commonly used datasets and metrics for neuron tracing bench testing. Oxford University Press 2022-10-27 /pmc/articles/PMC9750132/ /pubmed/36303315 http://dx.doi.org/10.1093/bioinformatics/btac712 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Liu, Yufeng Wang, Gaoyu Ascoli, Giorgio A Zhou, Jiangning Liu, Lijuan Neuron tracing from light microscopy images: automation, deep learning and bench testing |
title | Neuron tracing from light microscopy images: automation, deep learning and bench testing |
title_full | Neuron tracing from light microscopy images: automation, deep learning and bench testing |
title_fullStr | Neuron tracing from light microscopy images: automation, deep learning and bench testing |
title_full_unstemmed | Neuron tracing from light microscopy images: automation, deep learning and bench testing |
title_short | Neuron tracing from light microscopy images: automation, deep learning and bench testing |
title_sort | neuron tracing from light microscopy images: automation, deep learning and bench testing |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9750132/ https://www.ncbi.nlm.nih.gov/pubmed/36303315 http://dx.doi.org/10.1093/bioinformatics/btac712 |
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