| Segmentation and detection of fluorescent 3D spots. | |
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MedLine Citation:
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PMID: 22354758 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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The 3D spatial organization of genes and other genetic elements within the nucleus is important for regulating gene expression. Understanding how this spatial organization is established and maintained throughout the life of a cell is key to elucidating the many layers of gene regulation. Quantitative methods for studying nuclear organization will lead to insights into the molecular mechanisms that maintain gene organization as well as serve as diagnostic tools for pathologies caused by loss of nuclear structure. However, biologists currently lack automated and high throughput methods for quantitative and qualitative global analysis of 3D gene organization. In this study, we use confocal microscopy and fluorescence in-situ hybridization (FISH) as a cytogenetic technique to detect and localize the presence of specific DNA sequences in 3D. FISH uses probes that bind to specific targeted locations on the chromosomes, appearing as fluorescent spots in 3D images obtained using fluorescence microscopy. In this article, we propose an automated algorithm for segmentation and detection of 3D FISH spots. The algorithm is divided into two stages: spot segmentation and spot detection. Spot segmentation consists of 3D anisotropic smoothing to reduce the effect of noise, top-hat filtering, and intensity thresholding, followed by 3D region-growing. Spot detection uses a Bayesian classifier with spot features such as volume, average intensity, texture, and contrast to detect and classify the segmented spots as either true or false spots. Quantitative assessment of the proposed algorithm demonstrates improved segmentation and detection accuracy compared to other techniques. |
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Authors:
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Sundaresh Ram; Jeffrey J Rodríguez; Giovanni Bosco |
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Publication Detail:
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Type: Journal Article; Research Support, N.I.H., Extramural |
Journal Detail:
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Title: Cytometry. Part A : the journal of the International Society for Analytical Cytology Volume: 81 ISSN: 1552-4930 ISO Abbreviation: Cytometry A Publication Date: 2012 Mar |
Date Detail:
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Created Date: 2012-02-22 Completed Date: 2012-08-30 Revised Date: 2013-05-14 |
Medline Journal Info:
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Nlm Unique ID: 101235694 Medline TA: Cytometry A Country: United States |
Other Details:
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Languages: eng Pagination: 198-212 Citation Subset: IM |
Copyright Information:
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Copyright © 2012 International Society for Advancement of Cytometry. |
Affiliation:
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Department of Electrical and Computer Engineering, University of Arizona, Tucson, Arizona 85721, USA. |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms Anisotropy Bayes Theorem Cell Nucleus / chemistry Cytogenetic Analysis DNA / analysis* Image Processing, Computer-Assisted / methods Imaging, Three-Dimensional / methods* In Situ Hybridization, Fluorescence / methods* Microscopy, Confocal / methods* |
| Grant Support | |
ID/Acronym/Agency:
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GM069462/GM/NIGMS NIH HHS; R01 GM069462/GM/NIGMS NIH HHS; R01 GM069462-07/GM/NIGMS NIH HHS |
| Chemical | |
Reg. No./Substance:
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9007-49-2/DNA |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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