Joint estimation of water and fat images from magnetic resonance signals

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.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2010

Author dc:creator

• Hernando, Diego

Contributors dc:contributor

• Liang, Zhi-Pei
• Boppart, Stephen A.
• Bresler, Yoram
• Sutton, Bradley P.

• Magnetic Resonance Imaging (MRI)
• Joint estimation
• Fat-water
• Graph cuts
• Regularization
• Fat quantification

Statement dc:rights

• Copyright 2010 Diego Hernando

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/16833

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/16833