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Varying Collimation for Dark-Field Extraction
Although x-ray imaging is widely used in biomedical applications, biological soft tissues have small density changes, leading to low contrast resolution for attenuation-based x-ray imaging. Over the past years, x-ray small-angle scattering was studied as a new contrast mechanism to enhance subtle st...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2825654/ https://www.ncbi.nlm.nih.gov/pubmed/20182549 http://dx.doi.org/10.1155/2009/847537 |
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author | Wang, Ge Cong, Wenxiang Shen, Haiou Zou, Yu |
author_facet | Wang, Ge Cong, Wenxiang Shen, Haiou Zou, Yu |
author_sort | Wang, Ge |
collection | PubMed |
description | Although x-ray imaging is widely used in biomedical applications, biological soft tissues have small density changes, leading to low contrast resolution for attenuation-based x-ray imaging. Over the past years, x-ray small-angle scattering was studied as a new contrast mechanism to enhance subtle structural variation within the soft tissue. In this paper, we present a detection method to extract this type of x-ray scattering data, which are also referred to as dark-field signals. The key idea is to acquire an x-ray projection multiple times with varying collimation before an x-ray detector array. The projection data acquired with a collimator of a sufficiently high collimation aspect ratio contain mainly the primary beam with little scattering, while the data acquired with an appropriately reduced collimation aspect ratio include both the primary beam and small-angle scattering signals. Then, analysis of these corresponding datasets will produce desirable dark-field signals; for example, via digitally subtraction. In the numerical experiments, the feasibility of our dark-field detection technology is demonstrated in Monte Carlo simulation. The results show that the acquired dark field signals can clearly reveal the structural information of tissues in terms of Rayleigh scattering characteristics. |
format | Text |
id | pubmed-2825654 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-28256542010-02-24 Varying Collimation for Dark-Field Extraction Wang, Ge Cong, Wenxiang Shen, Haiou Zou, Yu Int J Biomed Imaging Research Article Although x-ray imaging is widely used in biomedical applications, biological soft tissues have small density changes, leading to low contrast resolution for attenuation-based x-ray imaging. Over the past years, x-ray small-angle scattering was studied as a new contrast mechanism to enhance subtle structural variation within the soft tissue. In this paper, we present a detection method to extract this type of x-ray scattering data, which are also referred to as dark-field signals. The key idea is to acquire an x-ray projection multiple times with varying collimation before an x-ray detector array. The projection data acquired with a collimator of a sufficiently high collimation aspect ratio contain mainly the primary beam with little scattering, while the data acquired with an appropriately reduced collimation aspect ratio include both the primary beam and small-angle scattering signals. Then, analysis of these corresponding datasets will produce desirable dark-field signals; for example, via digitally subtraction. In the numerical experiments, the feasibility of our dark-field detection technology is demonstrated in Monte Carlo simulation. The results show that the acquired dark field signals can clearly reveal the structural information of tissues in terms of Rayleigh scattering characteristics. Hindawi Publishing Corporation 2009 2010-02-16 /pmc/articles/PMC2825654/ /pubmed/20182549 http://dx.doi.org/10.1155/2009/847537 Text en Copyright © 2009 Ge Wang et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Wang, Ge Cong, Wenxiang Shen, Haiou Zou, Yu Varying Collimation for Dark-Field Extraction |
title | Varying Collimation for Dark-Field Extraction |
title_full | Varying Collimation for Dark-Field Extraction |
title_fullStr | Varying Collimation for Dark-Field Extraction |
title_full_unstemmed | Varying Collimation for Dark-Field Extraction |
title_short | Varying Collimation for Dark-Field Extraction |
title_sort | varying collimation for dark-field extraction |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2825654/ https://www.ncbi.nlm.nih.gov/pubmed/20182549 http://dx.doi.org/10.1155/2009/847537 |
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