2026-09-19T21:12:23Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/80837 2023-07-11 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

Liang, Zhi-Pei Ji, Jim Xiuquan 2015-09-25T20:08:24Z 2015-09-25T20:08:24Z 10000-01-01 2003 2003 The second part of this thesis addresses the problem of data acquisition and image reconstruction in data-sharing imaging. Specifically, two imaging techniques based on a generalized series (GS) model and a parallel data acquisition strategy are developed to improve imaging speed with a minimal concomitant loss of image quality. First, a new GS imaging method is presented which can effectively share information between different time frames of an image sequence. By optimizing the data acquisition scheme and the image reconstruction algorithm, we have successfully addressed the challenging problem of capturing transient dynamic features in the presence of nonrigid-body motions. Second, a new algorithm is proposed for image reconstruction from undersampled data acquired using multiple phased-array receiver coils. Specifically, wavelet denoising and motion compensation techniques are used to make the parallel imaging model more accurate. A support vector machine (SVM) regression method is developed to overcome the ill-conditioning of the model matrix. An adaptive scheme for choosing the regularization parameters is also proposed. Experimental results show that the proposed algorithm can reconstruct images with fewer artifacts and higher signal-to-noise ratios. This is particularly useful when data-sharing imaging is pushed to achieve very large acceleration factors. Made available in DSpace on 2015-09-25T20:08:24Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3101872.pdf: 5848724 bytes, checksum: 2727cc7b48c0903b91916ea3eeca103f (MD5) Previous issue date: 2003 Embargo set by: Seth Robbins for item 82119 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 132 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2003. http://hdl.handle.net/2142/80837 (MiAaPQ)AAI3101872 eng Engineering, Biomedical Fast Magnetic Resonance Imaging by Data Sharing: Generalized Series Imaging and Parallel Imaging text Electrical Engineering Electrical Engineering University of Illinois at Urbana-Champaign Dissertation Ph.D.