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Improved motion correction in brain MRI using 3D radial trajectory and projection moment analysis.

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Title: Improved motion correction in brain MRI using 3D radial trajectory and projection moment analysis.
Authors: Li, Bowen1,2 (AUTHOR), She, Huajun1,2 (AUTHOR) shehuajun@hotmail.com
Source: Magnetic Resonance in Medicine. Oct2024, Vol. 92 Issue 4, p1617-1631. 15p.
Subjects: Moments method (Statistics), Magnetic resonance imaging, Rigid bodies
Abstract: Purpose: To develop a generalized rigid body motion correction method in 3D radial brain MRI to deal with continuous motion pattern through projection moment analysis. Methods: An assumption was made that the multichannel coil moves with the head, which was achieved by using a flexible head coil. A two‐step motion correction scheme was proposed to directly extract the motion parameters from the acquired k‐space data using the analysis of center‐of‐mass with high noise robustness, which were used for retrospective motion correction. A recursive least‐squares model was introduced to recursively estimate the motion parameters for every single spoke, which used the smoothness of motion and resulted in high temporal resolution and low computational cost. Five volunteers were scanned at 3 T using a 3D radial multidimensional golden‐means trajectory with instructed motion patterns. The performance was tested through both simulation and in vivo experiments. Quantitative image quality metrics were calculated for comparison. Results: The proposed method showed good accuracy and precision in both translation and rotation estimation. A better result was achieved using the proposed two‐step correction compared to traditional one‐step correction without significantly increasing computation time. Retrospective correction showed substantial improvements in image quality among all scans, even for stationary scans. Conclusions: The proposed method provides an easy, robust, and time‐efficient tool for motion correction in brain MRI, which may benefit clinical diagnosis of uncooperative patients as well as scientific MRI researches. [ABSTRACT FROM AUTHOR]
Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Improved motion correction in brain MRI using 3D radial trajectory and projection moment analysis.
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  Data: <searchLink fieldCode="AR" term="%22Li%2C+Bowen%22">Li, Bowen</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22She%2C+Huajun%22">She, Huajun</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> shehuajun@hotmail.com</i>
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  Data: <searchLink fieldCode="JN" term="%22Magnetic+Resonance+in+Medicine%22">Magnetic Resonance in Medicine</searchLink>. Oct2024, Vol. 92 Issue 4, p1617-1631. 15p.
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  Data: <searchLink fieldCode="DE" term="%22Moments+method+%28Statistics%29%22">Moments method (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Magnetic+resonance+imaging%22">Magnetic resonance imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Rigid+bodies%22">Rigid bodies</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Purpose: To develop a generalized rigid body motion correction method in 3D radial brain MRI to deal with continuous motion pattern through projection moment analysis. Methods: An assumption was made that the multichannel coil moves with the head, which was achieved by using a flexible head coil. A two‐step motion correction scheme was proposed to directly extract the motion parameters from the acquired k‐space data using the analysis of center‐of‐mass with high noise robustness, which were used for retrospective motion correction. A recursive least‐squares model was introduced to recursively estimate the motion parameters for every single spoke, which used the smoothness of motion and resulted in high temporal resolution and low computational cost. Five volunteers were scanned at 3 T using a 3D radial multidimensional golden‐means trajectory with instructed motion patterns. The performance was tested through both simulation and in vivo experiments. Quantitative image quality metrics were calculated for comparison. Results: The proposed method showed good accuracy and precision in both translation and rotation estimation. A better result was achieved using the proposed two‐step correction compared to traditional one‐step correction without significantly increasing computation time. Retrospective correction showed substantial improvements in image quality among all scans, even for stationary scans. Conclusions: The proposed method provides an easy, robust, and time‐efficient tool for motion correction in brain MRI, which may benefit clinical diagnosis of uncooperative patients as well as scientific MRI researches. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1002/mrm.30159
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      – Code: eng
        Text: English
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      – SubjectFull: Moments method (Statistics)
        Type: general
      – SubjectFull: Magnetic resonance imaging
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      – SubjectFull: Rigid bodies
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              Text: Oct2024
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              Y: 2024
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