Huanzhou Yu1, Ann Shimakawa1,
Jean H. Brittain2, Charles A. McKenzie3, Scott B.
Reeder4
1Applied Science Laboratory, GE
Healthcare, Menlo Park, CA, United States; 2Applied Science
Laboratory, GE Healthcare, Madison, WI, United States; 3Department
of Medical Biophysics, University of Western Ontario, London, ON, Canada; 4Departments
of Radiology, Medical Physics, Biomedical Engineering and Medicine,
University of Wisconsin, Madison, Madison, WI, United States
Multi-point
water-fat separation methods must address the challenge of water-fat
ambiguity that arises from the signal behavior of water and fat which, when
both modeled with a single spectral peak, may appear identical in the
presence of Bo off-resonance. Water-fat ambiguity is typically removed by
enforcing field- or phase-map smoothness using region growing based
algorithms. However, the fat spectrum
actually has multiple spectral peaks. In this work, a novel algorithm to
identify water and fat for multi-point acquisitions is introduced by
exploiting the spectral differences between water and fat. New opportunities
arise to design algorithms for highly robust water-fat separation.