Theory and validation of magnetic resonance fluid motion estimation using intensity flow data.
BACKGROUND: Motion tracking based on spatial-temporal radio-frequency signals from the pixel representation of magnetic resonance (MR) imaging of a non-stationary fluid is able to provide two dimensional vector field maps. This supports the underlying fundamentals of magnetic resonance fluid motion...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2009-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC2651647?pdf=render |
| _version_ | 1818296408006983680 |
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| author | Kelvin Kian Loong Wong Richard Malcolm Kelso Stephen Grant Worthley Prashanthan Sanders Jagannath Mazumdar Derek Abbott |
| author_facet | Kelvin Kian Loong Wong Richard Malcolm Kelso Stephen Grant Worthley Prashanthan Sanders Jagannath Mazumdar Derek Abbott |
| author_sort | Kelvin Kian Loong Wong |
| collection | DOAJ |
| description | BACKGROUND: Motion tracking based on spatial-temporal radio-frequency signals from the pixel representation of magnetic resonance (MR) imaging of a non-stationary fluid is able to provide two dimensional vector field maps. This supports the underlying fundamentals of magnetic resonance fluid motion estimation and generates a new methodology for flow measurement that is based on registration of nuclear signals from moving hydrogen nuclei in fluid. However, there is a need to validate the computational aspect of the approach by using velocity flow field data that we will assume as the true reference information or ground truth. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we create flow vectors based on an ideal analytical vortex, and generate artificial signal-motion image data to verify our computational approach. The analytical and computed flow fields are compared to provide an error estimate of our methodology. The comparison shows that the fluid motion estimation approach using simulated MR data is accurate and robust enough for flow field mapping. To verify our methodology, we have tested the computational configuration on magnetic resonance images of cardiac blood and proved that the theory of magnetic resonance fluid motion estimation can be applicable practically. CONCLUSIONS/SIGNIFICANCE: The results of this work will allow us to progress further in the investigation of fluid motion prediction based on imaging modalities that do not require velocity encoding. This article describes a novel theory of motion estimation based on magnetic resonating blood, which may be directly applied to cardiac flow imaging. |
| first_indexed | 2024-12-13T04:03:03Z |
| format | Article |
| id | doaj.art-307f6cb253f5441a8d35ef247e3f588c |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-13T04:03:03Z |
| publishDate | 2009-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-307f6cb253f5441a8d35ef247e3f588c2022-12-22T00:00:22ZengPublic Library of Science (PLoS)PLoS ONE1932-62032009-01-0143e474710.1371/journal.pone.0004747Theory and validation of magnetic resonance fluid motion estimation using intensity flow data.Kelvin Kian Loong WongRichard Malcolm KelsoStephen Grant WorthleyPrashanthan SandersJagannath MazumdarDerek AbbottBACKGROUND: Motion tracking based on spatial-temporal radio-frequency signals from the pixel representation of magnetic resonance (MR) imaging of a non-stationary fluid is able to provide two dimensional vector field maps. This supports the underlying fundamentals of magnetic resonance fluid motion estimation and generates a new methodology for flow measurement that is based on registration of nuclear signals from moving hydrogen nuclei in fluid. However, there is a need to validate the computational aspect of the approach by using velocity flow field data that we will assume as the true reference information or ground truth. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we create flow vectors based on an ideal analytical vortex, and generate artificial signal-motion image data to verify our computational approach. The analytical and computed flow fields are compared to provide an error estimate of our methodology. The comparison shows that the fluid motion estimation approach using simulated MR data is accurate and robust enough for flow field mapping. To verify our methodology, we have tested the computational configuration on magnetic resonance images of cardiac blood and proved that the theory of magnetic resonance fluid motion estimation can be applicable practically. CONCLUSIONS/SIGNIFICANCE: The results of this work will allow us to progress further in the investigation of fluid motion prediction based on imaging modalities that do not require velocity encoding. This article describes a novel theory of motion estimation based on magnetic resonating blood, which may be directly applied to cardiac flow imaging.http://europepmc.org/articles/PMC2651647?pdf=render |
| spellingShingle | Kelvin Kian Loong Wong Richard Malcolm Kelso Stephen Grant Worthley Prashanthan Sanders Jagannath Mazumdar Derek Abbott Theory and validation of magnetic resonance fluid motion estimation using intensity flow data. PLoS ONE |
| title | Theory and validation of magnetic resonance fluid motion estimation using intensity flow data. |
| title_full | Theory and validation of magnetic resonance fluid motion estimation using intensity flow data. |
| title_fullStr | Theory and validation of magnetic resonance fluid motion estimation using intensity flow data. |
| title_full_unstemmed | Theory and validation of magnetic resonance fluid motion estimation using intensity flow data. |
| title_short | Theory and validation of magnetic resonance fluid motion estimation using intensity flow data. |
| title_sort | theory and validation of magnetic resonance fluid motion estimation using intensity flow data |
| url | http://europepmc.org/articles/PMC2651647?pdf=render |
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