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Abstract #0566

JIGSAW: Joint Inhomogeneity Estimation Via Global Segment Assembly for Water-Fat Separation

Yi Lu1, Wenmiao Lu2, Brian Andrew Hargreaves3

1Electrical Engineering, Stanford University, Stanford, CA, USA; 2Electrical & Electronic Engr., Nanyang Technological University, Singapore, Singapore; 3Radiology, Stanford University, Stanford, CA, USA

Key to the success of three-point water-fat separation is reliable estimation of field inhomogeneities, which remains difficult in many clinical applications. The difficulty arises when the spectral field-of-view is not sufficient to accommodate the field inhomogeneities, causing aliasing. This work describes a novel field map estimation technique called JIGSAW, which is based on belief propagation (BP) to produce large segments of pixels with smooth field map values. The field map estimation problem is then reduced to the assembly of a few large segments. In vivo results show that JIGSAW correctly resolves field inhomogeneities in the presence of spectral aliasing.