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DEFiNE: A Method for Enhancement and Quantification of Fluorescently Labeled Axons

Visualization and quantification of fluorescently labeled axonal fibers are widely employed in studies of neuronal connectivity in the brain. However, accurate analysis of axon density is often confounded by autofluorescence and other fluorescent artifacts. By the time these problems are detected in...

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Autores principales: Powell, Jeanne M., Plummer, Nicholas W., Scappini, Erica L., Tucker, Charles J., Jensen, Patricia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6336715/
https://www.ncbi.nlm.nih.gov/pubmed/30687025
http://dx.doi.org/10.3389/fnana.2018.00117
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author Powell, Jeanne M.
Plummer, Nicholas W.
Scappini, Erica L.
Tucker, Charles J.
Jensen, Patricia
author_facet Powell, Jeanne M.
Plummer, Nicholas W.
Scappini, Erica L.
Tucker, Charles J.
Jensen, Patricia
author_sort Powell, Jeanne M.
collection PubMed
description Visualization and quantification of fluorescently labeled axonal fibers are widely employed in studies of neuronal connectivity in the brain. However, accurate analysis of axon density is often confounded by autofluorescence and other fluorescent artifacts. By the time these problems are detected in labeled tissue sections, significant time and resources have been invested, and the tissue may not be easy to replace. In response to these difficulties, we have developed Digital Enhancement of Fibers with Noise Elimination (DEFiNE), a method for eliminating fluorescent artifacts from digital images based on their morphology and fluorescence spectrum, thus permitting enhanced visualization and quantification of axonal fibers. Application of this method is facilitated by a DEFiNE macro, written using ImageJ Macro Language (IJM), which includes an automated and customizable procedure for image processing and a semi-automated quantification method that accounts for any remaining local variation in background intensity. The DEFiNE macro is open-source and used with the widely available FIJI software for maximum accessibility.
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spelling pubmed-63367152019-01-25 DEFiNE: A Method for Enhancement and Quantification of Fluorescently Labeled Axons Powell, Jeanne M. Plummer, Nicholas W. Scappini, Erica L. Tucker, Charles J. Jensen, Patricia Front Neuroanat Neuroscience Visualization and quantification of fluorescently labeled axonal fibers are widely employed in studies of neuronal connectivity in the brain. However, accurate analysis of axon density is often confounded by autofluorescence and other fluorescent artifacts. By the time these problems are detected in labeled tissue sections, significant time and resources have been invested, and the tissue may not be easy to replace. In response to these difficulties, we have developed Digital Enhancement of Fibers with Noise Elimination (DEFiNE), a method for eliminating fluorescent artifacts from digital images based on their morphology and fluorescence spectrum, thus permitting enhanced visualization and quantification of axonal fibers. Application of this method is facilitated by a DEFiNE macro, written using ImageJ Macro Language (IJM), which includes an automated and customizable procedure for image processing and a semi-automated quantification method that accounts for any remaining local variation in background intensity. The DEFiNE macro is open-source and used with the widely available FIJI software for maximum accessibility. Frontiers Media S.A. 2019-01-11 /pmc/articles/PMC6336715/ /pubmed/30687025 http://dx.doi.org/10.3389/fnana.2018.00117 Text en Copyright © 2019 At least a portion of this work is authored by Powell, Plummer, Scappini, Tucker and Jensen on behalf of the U.S. Government and, as regards. Powell, Plummer, Scappini, Tucker and Jensen and the US government, is not subject to copyright protection in the United States. http://creativecommons.org/licenses/by/4.0/ S. Government and, as regards Powell, Plummer, Scappini, Tucker, Jensen, and the US government, is not subject to copyright protection in the United States. Foreign and other copyrights may apply. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Powell, Jeanne M.
Plummer, Nicholas W.
Scappini, Erica L.
Tucker, Charles J.
Jensen, Patricia
DEFiNE: A Method for Enhancement and Quantification of Fluorescently Labeled Axons
title DEFiNE: A Method for Enhancement and Quantification of Fluorescently Labeled Axons
title_full DEFiNE: A Method for Enhancement and Quantification of Fluorescently Labeled Axons
title_fullStr DEFiNE: A Method for Enhancement and Quantification of Fluorescently Labeled Axons
title_full_unstemmed DEFiNE: A Method for Enhancement and Quantification of Fluorescently Labeled Axons
title_short DEFiNE: A Method for Enhancement and Quantification of Fluorescently Labeled Axons
title_sort define: a method for enhancement and quantification of fluorescently labeled axons
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6336715/
https://www.ncbi.nlm.nih.gov/pubmed/30687025
http://dx.doi.org/10.3389/fnana.2018.00117
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