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Denoising and Reconstruction Methods for Echo Planar Imaging : = Applications on a High-Performance Compact 3T MRI System.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Denoising and Reconstruction Methods for Echo Planar Imaging :/
Reminder of title:
Applications on a High-Performance Compact 3T MRI System.
Author:
Meyer, Nolan Kohrell.
Description:
1 online resource (156 pages)
Notes:
Source: Dissertations Abstracts International, Volume: 84-08, Section: B.
Contained By:
Dissertations Abstracts International84-08B.
Subject:
Biomedical engineering. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30250181click for full text (PQDT)
ISBN:
9798374404432
Denoising and Reconstruction Methods for Echo Planar Imaging : = Applications on a High-Performance Compact 3T MRI System.
Meyer, Nolan Kohrell.
Denoising and Reconstruction Methods for Echo Planar Imaging :
Applications on a High-Performance Compact 3T MRI System. - 1 online resource (156 pages)
Source: Dissertations Abstracts International, Volume: 84-08, Section: B.
Thesis (Ph.D.)--College of Medicine - Mayo Clinic, 2023.
Includes bibliographical references
Magnetic resonance imaging (MRI) is a powerful and versatile imaging modality which, as a rich subfield of physics and signal processing, has become indispensible both in the clinic and the scientific laboratory. While MRI has many capabilities in enabling visualization of structural and functional tissue properties, it has a practical cost: scan time. Echo planar imaging (EPI) is a longstanding fast measurement strategy in MRI facilitating numerous advanced applications of MRI including structural and functional imaging. However, the EPI signal is sensitive to system non-idealities and is limited in signal to noise ratio (SNR).Reconstruction methods not explicitly accounting for these effects produce image artifacts, limiting diagnostic and neuroscientific utility of EPI.The Compact 3T MRI system, developed in collaboration between Mayo Clinic and GE Global Research, is a prototype scanner with a high-performance gradient system enabling dramatically reduced echo spacing. EPI applications synergize very well with the Compact3T. Data for studies in this dissertation were acquired on this system. As these are data with imaging parameters difficult or impossible to obtain on a whole-body scanner at 3T, they were in their own way state-of-the-art. This, combined with the methods introduced in this thesis, yielded novel and significant results.In this dissertation, denoising of dynamic EPI image data for functional MRI (fMRI)is explored. For both clinical task-based fMRI and multi-echo resting-state fMRI, locally low-rankedness (LLR) is used as a prior for suppression of spurious noise from temporal image volumes.Toward EPI-based structural imaging, model-based iterative reconstruction (MBIR) is investigated for multi-shot, point spread function (PSF)-encoded EPI. A signal model is developed leveraging properties known a priori, and its algebraic structure is leveraged to develop an efficient iterative reconstruction. MBIR is demonstrated to yield superior image quality relative to standard methods and introduce nonstandard sampling opportunities.In three chapters each documenting a completed project, image denoising or reconstruction methods are demonstrated. In each study, our methods yield superior results from full datasets, and comparable or superior results from truncated datasets-suggesting these works are enabling technologies toward clinical scan time reduction for EPI-based applications on a high-performance 3T scanner.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023
Mode of access: World Wide Web
ISBN: 9798374404432Subjects--Topical Terms:
535387
Biomedical engineering.
Subjects--Index Terms:
Functional MRIIndex Terms--Genre/Form:
542853
Electronic books.
Denoising and Reconstruction Methods for Echo Planar Imaging : = Applications on a High-Performance Compact 3T MRI System.
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Source: Dissertations Abstracts International, Volume: 84-08, Section: B.
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Magnetic resonance imaging (MRI) is a powerful and versatile imaging modality which, as a rich subfield of physics and signal processing, has become indispensible both in the clinic and the scientific laboratory. While MRI has many capabilities in enabling visualization of structural and functional tissue properties, it has a practical cost: scan time. Echo planar imaging (EPI) is a longstanding fast measurement strategy in MRI facilitating numerous advanced applications of MRI including structural and functional imaging. However, the EPI signal is sensitive to system non-idealities and is limited in signal to noise ratio (SNR).Reconstruction methods not explicitly accounting for these effects produce image artifacts, limiting diagnostic and neuroscientific utility of EPI.The Compact 3T MRI system, developed in collaboration between Mayo Clinic and GE Global Research, is a prototype scanner with a high-performance gradient system enabling dramatically reduced echo spacing. EPI applications synergize very well with the Compact3T. Data for studies in this dissertation were acquired on this system. As these are data with imaging parameters difficult or impossible to obtain on a whole-body scanner at 3T, they were in their own way state-of-the-art. This, combined with the methods introduced in this thesis, yielded novel and significant results.In this dissertation, denoising of dynamic EPI image data for functional MRI (fMRI)is explored. For both clinical task-based fMRI and multi-echo resting-state fMRI, locally low-rankedness (LLR) is used as a prior for suppression of spurious noise from temporal image volumes.Toward EPI-based structural imaging, model-based iterative reconstruction (MBIR) is investigated for multi-shot, point spread function (PSF)-encoded EPI. A signal model is developed leveraging properties known a priori, and its algebraic structure is leveraged to develop an efficient iterative reconstruction. MBIR is demonstrated to yield superior image quality relative to standard methods and introduce nonstandard sampling opportunities.In three chapters each documenting a completed project, image denoising or reconstruction methods are demonstrated. In each study, our methods yield superior results from full datasets, and comparable or superior results from truncated datasets-suggesting these works are enabling technologies toward clinical scan time reduction for EPI-based applications on a high-performance 3T scanner.
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