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Computational tools for automated histological image analysis and quantification in cardiac tissue
Image processing and quantification is a routine and important task across disciplines in biomedical research. Understanding the effects of disease on the tissue and organ level often requires the use of images, however the process of interpreting those images into data which can be tested for signi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6931069/ https://www.ncbi.nlm.nih.gov/pubmed/31890644 http://dx.doi.org/10.1016/j.mex.2019.11.028 |
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author | Gratz, Daniel Winkle, Alexander J. Dalic, Alyssa Unudurthi, Sathya D. Hund, Thomas J. |
author_facet | Gratz, Daniel Winkle, Alexander J. Dalic, Alyssa Unudurthi, Sathya D. Hund, Thomas J. |
author_sort | Gratz, Daniel |
collection | PubMed |
description | Image processing and quantification is a routine and important task across disciplines in biomedical research. Understanding the effects of disease on the tissue and organ level often requires the use of images, however the process of interpreting those images into data which can be tested for significance is often time intensive, tedious and prone to inaccuracy or bias. When working within resource constraints, these different issues often present a trade-off between time invested in analysis and accuracy. To address these issues, we present two novel open source and publically available tools for automated analysis of histological cardiac tissue samples: • Automated Fibrosis Analysis Tool (AFAT) for quantifying fibrosis; and • Macrophage Analysis Tool (MAT) for quantifying infiltrating macrophages. |
format | Online Article Text |
id | pubmed-6931069 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-69310692019-12-30 Computational tools for automated histological image analysis and quantification in cardiac tissue Gratz, Daniel Winkle, Alexander J. Dalic, Alyssa Unudurthi, Sathya D. Hund, Thomas J. MethodsX Medicine and Dentistry Image processing and quantification is a routine and important task across disciplines in biomedical research. Understanding the effects of disease on the tissue and organ level often requires the use of images, however the process of interpreting those images into data which can be tested for significance is often time intensive, tedious and prone to inaccuracy or bias. When working within resource constraints, these different issues often present a trade-off between time invested in analysis and accuracy. To address these issues, we present two novel open source and publically available tools for automated analysis of histological cardiac tissue samples: • Automated Fibrosis Analysis Tool (AFAT) for quantifying fibrosis; and • Macrophage Analysis Tool (MAT) for quantifying infiltrating macrophages. Elsevier 2019-12-07 /pmc/articles/PMC6931069/ /pubmed/31890644 http://dx.doi.org/10.1016/j.mex.2019.11.028 Text en © 2019 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Medicine and Dentistry Gratz, Daniel Winkle, Alexander J. Dalic, Alyssa Unudurthi, Sathya D. Hund, Thomas J. Computational tools for automated histological image analysis and quantification in cardiac tissue |
title | Computational tools for automated histological image analysis and quantification in cardiac tissue |
title_full | Computational tools for automated histological image analysis and quantification in cardiac tissue |
title_fullStr | Computational tools for automated histological image analysis and quantification in cardiac tissue |
title_full_unstemmed | Computational tools for automated histological image analysis and quantification in cardiac tissue |
title_short | Computational tools for automated histological image analysis and quantification in cardiac tissue |
title_sort | computational tools for automated histological image analysis and quantification in cardiac tissue |
topic | Medicine and Dentistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6931069/ https://www.ncbi.nlm.nih.gov/pubmed/31890644 http://dx.doi.org/10.1016/j.mex.2019.11.028 |
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