"This thesis proposes two techniques, namely Compressed Sensing (CS) and self-gating, for pre-clinical (CMRI) to reduce scan time and RF exposure to mouse heart, simply experimental procedures, and improve imaging quality. The proposed CS technique reduces the number of radial trajectories in Ultra-short Echo Time (UTE) CMRI scans on a 7 Tesla MRI machine to acquire 13% to 38% of the fully sampled k-space data. To reconstruct the image, the Non-Uniform Fast Fourier Transform (NUFFT) is utilized in each iteration of the l1-norm optimization algorithm of the CS to reduce error and aliasing. Experimental results with a phantom and a mouse heart samples show that the image quality of the proposed NUFFT-CS reconstructions, measured by the Peak Signal to Noise ratio (PSNR) and structural similarity (SSIM), is obviously better than those of traditional zero-filling method and regridding-CS method. Comparing the images of the CS technique with the reconstructions of fully sampled data, the quality degradation is illegible while the scan time is largely reduced.
The proposed self-gating technique extracts the cardiac cycle information directly from the UTE CMRI measurements that are acquired without Electrocardiography (ECG) trigger. The proposed detector filters the k0 lines in the no-trigger UTE MRI scans to extract the cardiac cycle features, and automatically detects the peaks of the filtered signal as the cycle start points. The reconstruct cardiac images based on the self-gating signals reflect the cardiac cycle clearly and the scan time in MRI exams is reduced by 40% to 70%. The proposed self-gating detector differs from existing k0-line detector in the filter design and in the combination with NUFFT image reconstruction. Future research in this direction may include thorough analysis of the detector performance and may combine self-gated MRI with CS reconstruction."--Abstract, page iv.
Zheng, Y. Rosa
Grant, Steven L.
Moss, Randy Hays, 1953-
Electrical and Computer Engineering
M.S. in Electrical Engineering
Missouri University of Science and Technology
Journal article titles appearing in thesis/dissertation
- Compressed sensing with non-uniform fast Fourier transform for radial Ultra-Short Echo Time (UTE) MRI
- Automated cardiac self-gated radial CMRI
viii, 36 pages
© 2015 Xiahan Yang, All rights reserved.
Thesis - Open Access
Magnetic resonance imaging -- Data processing
Electronic OCLC #
Link to Catalog Record
Yang, Xiahan, "Compressed sensing techniques for radial Ultra-short Echo Time (UTE) magnetic resonance imaging" (2015). Masters Theses. 7422.