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Movement correction in DCE-MRI through windowed and reconstruction dynamic mode decomposition
Images of the kidneys using dynamic contrast-enhanced magnetic resonance renography (DCE-MRR) contains unwanted complex organ motion due to respiration. This gives rise to motion artefacts that hinder the clinical assessment of kidney function. However, due to the rapid change in contrast agent with...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7010382/ https://www.ncbi.nlm.nih.gov/pubmed/32103860 http://dx.doi.org/10.1007/s00138-017-0835-5 |
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author | Tirunagari, Santosh Poh, Norman Wells, Kevin Bober, Miroslaw Gorden, Isky Windridge, David |
author_facet | Tirunagari, Santosh Poh, Norman Wells, Kevin Bober, Miroslaw Gorden, Isky Windridge, David |
author_sort | Tirunagari, Santosh |
collection | PubMed |
description | Images of the kidneys using dynamic contrast-enhanced magnetic resonance renography (DCE-MRR) contains unwanted complex organ motion due to respiration. This gives rise to motion artefacts that hinder the clinical assessment of kidney function. However, due to the rapid change in contrast agent within the DCE-MR image sequence, commonly used intensity-based image registration techniques are likely to fail. While semi-automated approaches involving human experts are a possible alternative, they pose significant drawbacks including inter-observer variability, and the bottleneck introduced through manual inspection of the multiplicity of images produced during a DCE-MRR study. To address this issue, we present a novel automated, registration-free movement correction approach based on windowed and reconstruction variants of dynamic mode decomposition (WR-DMD). Our proposed method is validated on ten different healthy volunteers’ kidney DCE-MRI data sets. The results, using block-matching-block evaluation on the image sequence produced by WR-DMD, show the elimination of [Formula: see text] of mean motion magnitude when compared to the original data sets, thereby demonstrating the viability of automatic movement correction using WR-DMD. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00138-017-0835-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-7010382 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-70103822020-02-24 Movement correction in DCE-MRI through windowed and reconstruction dynamic mode decomposition Tirunagari, Santosh Poh, Norman Wells, Kevin Bober, Miroslaw Gorden, Isky Windridge, David Mach Vis Appl Original Paper Images of the kidneys using dynamic contrast-enhanced magnetic resonance renography (DCE-MRR) contains unwanted complex organ motion due to respiration. This gives rise to motion artefacts that hinder the clinical assessment of kidney function. However, due to the rapid change in contrast agent within the DCE-MR image sequence, commonly used intensity-based image registration techniques are likely to fail. While semi-automated approaches involving human experts are a possible alternative, they pose significant drawbacks including inter-observer variability, and the bottleneck introduced through manual inspection of the multiplicity of images produced during a DCE-MRR study. To address this issue, we present a novel automated, registration-free movement correction approach based on windowed and reconstruction variants of dynamic mode decomposition (WR-DMD). Our proposed method is validated on ten different healthy volunteers’ kidney DCE-MRI data sets. The results, using block-matching-block evaluation on the image sequence produced by WR-DMD, show the elimination of [Formula: see text] of mean motion magnitude when compared to the original data sets, thereby demonstrating the viability of automatic movement correction using WR-DMD. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00138-017-0835-5) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2017-04-06 2017 /pmc/articles/PMC7010382/ /pubmed/32103860 http://dx.doi.org/10.1007/s00138-017-0835-5 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Paper Tirunagari, Santosh Poh, Norman Wells, Kevin Bober, Miroslaw Gorden, Isky Windridge, David Movement correction in DCE-MRI through windowed and reconstruction dynamic mode decomposition |
title | Movement correction in DCE-MRI through windowed and reconstruction dynamic mode decomposition |
title_full | Movement correction in DCE-MRI through windowed and reconstruction dynamic mode decomposition |
title_fullStr | Movement correction in DCE-MRI through windowed and reconstruction dynamic mode decomposition |
title_full_unstemmed | Movement correction in DCE-MRI through windowed and reconstruction dynamic mode decomposition |
title_short | Movement correction in DCE-MRI through windowed and reconstruction dynamic mode decomposition |
title_sort | movement correction in dce-mri through windowed and reconstruction dynamic mode decomposition |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7010382/ https://www.ncbi.nlm.nih.gov/pubmed/32103860 http://dx.doi.org/10.1007/s00138-017-0835-5 |
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