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Deconvolution-Based CT and MR Brain Perfusion Measurement: Theoretical Model Revisited and Practical Implementation Details
Deconvolution-based analysis of CT and MR brain perfusion data is widely used in clinical practice and it is still a topic of ongoing research activities. In this paper, we present a comprehensive derivation and explanation of the underlying physiological model for intravascular tracer systems. We a...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3166726/ https://www.ncbi.nlm.nih.gov/pubmed/21904538 http://dx.doi.org/10.1155/2011/467563 |
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author | Fieselmann, Andreas Kowarschik, Markus Ganguly, Arundhuti Hornegger, Joachim Fahrig, Rebecca |
author_facet | Fieselmann, Andreas Kowarschik, Markus Ganguly, Arundhuti Hornegger, Joachim Fahrig, Rebecca |
author_sort | Fieselmann, Andreas |
collection | PubMed |
description | Deconvolution-based analysis of CT and MR brain perfusion data is widely used in clinical practice and it is still a topic of ongoing research activities. In this paper, we present a comprehensive derivation and explanation of the underlying physiological model for intravascular tracer systems. We also discuss practical details that are needed to properly implement algorithms for perfusion analysis. Our description of the practical computer implementation is focused on the most frequently employed algebraic deconvolution methods based on the singular value decomposition. In particular, we further discuss the need for regularization in order to obtain physiologically reasonable results. We include an overview of relevant preprocessing steps and provide numerous references to the literature. We cover both CT and MR brain perfusion imaging in this paper because they share many common aspects. The combination of both the theoretical as well as the practical aspects of perfusion analysis explicitly emphasizes the simplifications to the underlying physiological model that are necessary in order to apply it to measured data acquired with current CT and MR scanners. |
format | Online Article Text |
id | pubmed-3166726 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-31667262011-09-08 Deconvolution-Based CT and MR Brain Perfusion Measurement: Theoretical Model Revisited and Practical Implementation Details Fieselmann, Andreas Kowarschik, Markus Ganguly, Arundhuti Hornegger, Joachim Fahrig, Rebecca Int J Biomed Imaging Review Article Deconvolution-based analysis of CT and MR brain perfusion data is widely used in clinical practice and it is still a topic of ongoing research activities. In this paper, we present a comprehensive derivation and explanation of the underlying physiological model for intravascular tracer systems. We also discuss practical details that are needed to properly implement algorithms for perfusion analysis. Our description of the practical computer implementation is focused on the most frequently employed algebraic deconvolution methods based on the singular value decomposition. In particular, we further discuss the need for regularization in order to obtain physiologically reasonable results. We include an overview of relevant preprocessing steps and provide numerous references to the literature. We cover both CT and MR brain perfusion imaging in this paper because they share many common aspects. The combination of both the theoretical as well as the practical aspects of perfusion analysis explicitly emphasizes the simplifications to the underlying physiological model that are necessary in order to apply it to measured data acquired with current CT and MR scanners. Hindawi Publishing Corporation 2011 2011-08-28 /pmc/articles/PMC3166726/ /pubmed/21904538 http://dx.doi.org/10.1155/2011/467563 Text en Copyright © 2011 Andreas Fieselmann 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 | Review Article Fieselmann, Andreas Kowarschik, Markus Ganguly, Arundhuti Hornegger, Joachim Fahrig, Rebecca Deconvolution-Based CT and MR Brain Perfusion Measurement: Theoretical Model Revisited and Practical Implementation Details |
title | Deconvolution-Based CT and MR Brain Perfusion Measurement: Theoretical Model Revisited and Practical Implementation Details |
title_full | Deconvolution-Based CT and MR Brain Perfusion Measurement: Theoretical Model Revisited and Practical Implementation Details |
title_fullStr | Deconvolution-Based CT and MR Brain Perfusion Measurement: Theoretical Model Revisited and Practical Implementation Details |
title_full_unstemmed | Deconvolution-Based CT and MR Brain Perfusion Measurement: Theoretical Model Revisited and Practical Implementation Details |
title_short | Deconvolution-Based CT and MR Brain Perfusion Measurement: Theoretical Model Revisited and Practical Implementation Details |
title_sort | deconvolution-based ct and mr brain perfusion measurement: theoretical model revisited and practical implementation details |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3166726/ https://www.ncbi.nlm.nih.gov/pubmed/21904538 http://dx.doi.org/10.1155/2011/467563 |
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