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oai:www.ideals.illinois.edu:2142/16833 2023-07-10 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

Liang, Zhi-Pei Liang, Zhi-Pei Boppart, Stephen A. Bresler, Yoram Sutton, Bradley P. Hernando, Diego 2010-08-20T17:59:17Z 2010-08-20T17:59:17Z 2010-08-20T17:59:17Z 2010-08 Fat-water separation is a classical problem for in vivo magnetic resonance imaging, with multiple applications both in cases where the aim is the removal of fat signal, as well as in cases where the fat signal itself is of diagnostic interest. Although many methods have been proposed, robust fat-water separation remains a challenge. The problem presents two key difficulties: (a) the presence of B0 field inhomogeneities, which makes the problem non-linear and ill-posed; and (b) the difficulty of accurately modeling the acquired signal, which can lead to bias in quantitative fat-water separation applications. The research in this thesis has developed joint estimation methods to address the ill-posedness of the problem by simultaneously estimating the complete fat-water images and field inhomogeneity map. The joint estimation formulation developed in this work is able to overcome the complications of voxel-by-voxel separation, and it allows characterization of the resolution properties of its estimates, but results in a challenging optimization problem. To address this complication, optimization algorithms based on graph cuts have been developed and studied. Additionally, this work addresses the modeling issues of fat-water separation by comparing a set of recently proposed models, demonstrating that accurate spectral modeling of the acquired signal is critical for quantitative applications. Simulation, phantom and in vivo results are included to highlight the properties of the proposed methods and compare them to previous approaches. This thesis also contains example applications of the proposed methods, with an emphasis on the characterization of intramyocardial fat. Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2010-06-28T15:31:42Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Hernando_Diego.pdf: 2789616 bytes, checksum: 5b5c8a640e8eb2037cff801389cca424 (MD5) Made available in DSpace on 2010-08-20T17:59:17Z (GMT). No. of bitstreams: 2 Hernando_Diego.pdf: 2789616 bytes, checksum: 5b5c8a640e8eb2037cff801389cca424 (MD5) license.txt: 4064 bytes, checksum: f22ba43cb0b6431b9b5558a19e1ad04a (MD5) http://hdl.handle.net/2142/16833 en Copyright 2010 Diego Hernando Magnetic Resonance Imaging (MRI) Joint estimation Fat-water Graph cuts Regularization Fat quantification Joint estimation of water and fat images from magnetic resonance signals Electrical & Computer Eng 1933 Electrical & Computer Engr 1200 University of Illinois at Urbana-Champaign Dissertation Ph.D. PHD:Electr & Computer Eng-UIUC 10KS1200PHD