Scan acceleration and motion correction for cardiovascular magnetic resonance imaging
Abstract/Contents
- Abstract
- Magnetic resonance imaging (MRI) is a powerful medical imaging modality providing excellent soft-tissue contrast without exposing the patient to ionizing radiation. In particular, MRI plays a critical role in the diagnosis and management of cardiovascular disease with the possibility of obtaining a wide range of anatomical and functional information in a single examination. However, despite technical advancements such as parallel imaging and compressed sensing, the scan time of cardiovascular MRI is still relatively long compared to X-ray or CT. The temporal resolution for functional assessment is limited, and compensation for respiratory and cardiac motion remains challenging. To improve the temporal resolution, an undersampling acquisition scheme and a low-rank matrix-completion reconstruction method recovering the missing data are developed and applied to perfusion imaging in the lower extremities. To exploit the spatial-temporal information redundancy, the proposed method formulates the image construction as an optimization problem with the low-rank constraint and the data-consistency constraint. With the proposed method, dynamic contrast-enhanced perfusion imaging in the lower extremities with high temporal resolution (< 3 s) and volumetric coverage (> 32x16x32 cm3) is achieved. Pulse sequence design is another approach to achieve scan acceleration. Recognizing that the region of interest (ROI) is smaller than the full spatial extent of the anatomy in coronary magnetic resonance angiography (MRA), a new magnetization preparation sequence that combines outer volume suppression with T2 preparation is designed and implemented, enabling accelerated free-breathing whole-heart coronary MRA with enhanced blood-myocardium contrast in a scan time of less than 3 minutes by reducing the image field-of-view. Two nonrigid motion-correction methods are also developed to reduce the motion artifacts generated during the scan. These two methods extract several motion trajectories from 3D image-based navigators (iNAVs) and compensate for them with an autofocusing algorithm. A bank of motion-corrected images is generated by motion correction with every motion trajectory, and the final image is assembled on a pixel-by-pixel basis with the best-focused pixel chosen from the bank of images according to a localized gradient entropy metric. The first method is developed for free-breathing whole-heart coronary MRA in which the motion is complicated and nonrigid. Both global rigid motion and localized nonrigid motion are extracted from the 3D iNAVs. The second method is designed for abdominal MRA, in which the imaging volume is divided into ROIs with different 3D translational motion patterns. An automatic ROI-clustering method is developed and a translational motion trajectory is estimated for every ROI. Both motion correction methods demonstrate improved vessel sharpness in the in vivo studies. The image reconstruction method, pulse sequence and motion-correction methods developed enable scan acceleration and motion correction to address several challenges in cardiovascular MRI. These methods show promise of extending the diagnostic utility of MRI in this application.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2015 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Luo, Jieying |
|---|---|
| Associated with | Stanford University, Department of Electrical Engineering. |
| Primary advisor | Nishimura, Dwight George |
| Thesis advisor | Nishimura, Dwight George |
| Thesis advisor | McConnell, Michael |
| Thesis advisor | Pauly, John (John M.) |
| Advisor | McConnell, Michael |
| Advisor | Pauly, John (John M.) |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Jieying Luo. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2015. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2015 by Jieying Luo
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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