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Wndchrm – an open source utility for biological image analysis
BACKGROUND: Biological imaging is an emerging field, covering a wide range of applications in biological and clinical research. However, while machinery for automated experimenting and data acquisition has been developing rapidly in the past years, automated image analysis often introduces a bottlen...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2478650/ https://www.ncbi.nlm.nih.gov/pubmed/18611266 http://dx.doi.org/10.1186/1751-0473-3-13 |
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author | Shamir, Lior Orlov, Nikita Eckley, D Mark Macura, Tomasz Johnston, Josiah Goldberg, Ilya G |
author_facet | Shamir, Lior Orlov, Nikita Eckley, D Mark Macura, Tomasz Johnston, Josiah Goldberg, Ilya G |
author_sort | Shamir, Lior |
collection | PubMed |
description | BACKGROUND: Biological imaging is an emerging field, covering a wide range of applications in biological and clinical research. However, while machinery for automated experimenting and data acquisition has been developing rapidly in the past years, automated image analysis often introduces a bottleneck in high content screening. METHODS: Wndchrm is an open source utility for biological image analysis. The software works by first extracting image content descriptors from the raw image, image transforms, and compound image transforms. Then, the most informative features are selected, and the feature vector of each image is used for classification and similarity measurement. RESULTS: Wndchrm has been tested using several publicly available biological datasets, and provided results which are favorably comparable to the performance of task-specific algorithms developed for these datasets. The simple user interface allows researchers who are not knowledgeable in computer vision methods and have no background in computer programming to apply image analysis to their data. CONCLUSION: We suggest that wndchrm can be effectively used for a wide range of biological image analysis tasks. Using wndchrm can allow scientists to perform automated biological image analysis while avoiding the costly challenge of implementing computer vision and pattern recognition algorithms. |
format | Text |
id | pubmed-2478650 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-24786502008-07-22 Wndchrm – an open source utility for biological image analysis Shamir, Lior Orlov, Nikita Eckley, D Mark Macura, Tomasz Johnston, Josiah Goldberg, Ilya G Source Code Biol Med Research BACKGROUND: Biological imaging is an emerging field, covering a wide range of applications in biological and clinical research. However, while machinery for automated experimenting and data acquisition has been developing rapidly in the past years, automated image analysis often introduces a bottleneck in high content screening. METHODS: Wndchrm is an open source utility for biological image analysis. The software works by first extracting image content descriptors from the raw image, image transforms, and compound image transforms. Then, the most informative features are selected, and the feature vector of each image is used for classification and similarity measurement. RESULTS: Wndchrm has been tested using several publicly available biological datasets, and provided results which are favorably comparable to the performance of task-specific algorithms developed for these datasets. The simple user interface allows researchers who are not knowledgeable in computer vision methods and have no background in computer programming to apply image analysis to their data. CONCLUSION: We suggest that wndchrm can be effectively used for a wide range of biological image analysis tasks. Using wndchrm can allow scientists to perform automated biological image analysis while avoiding the costly challenge of implementing computer vision and pattern recognition algorithms. BioMed Central 2008-07-08 /pmc/articles/PMC2478650/ /pubmed/18611266 http://dx.doi.org/10.1186/1751-0473-3-13 Text en Copyright © 2008 Shamir et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Shamir, Lior Orlov, Nikita Eckley, D Mark Macura, Tomasz Johnston, Josiah Goldberg, Ilya G Wndchrm – an open source utility for biological image analysis |
title | Wndchrm – an open source utility for biological image analysis |
title_full | Wndchrm – an open source utility for biological image analysis |
title_fullStr | Wndchrm – an open source utility for biological image analysis |
title_full_unstemmed | Wndchrm – an open source utility for biological image analysis |
title_short | Wndchrm – an open source utility for biological image analysis |
title_sort | wndchrm – an open source utility for biological image analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2478650/ https://www.ncbi.nlm.nih.gov/pubmed/18611266 http://dx.doi.org/10.1186/1751-0473-3-13 |
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