title: Compressed sensing for chemical shift-based water-fat separation.
abstract: Multi echo chemical shift-based water-fat separation methods allow for uniform fat suppression in the presence of main field inhomogeneities. However, these methods require additional scan time for chemical shift encoding. This work presents a method for water-fat separation from undersampled data (CS-WF), which combines compressed sensing and chemical shift-based water-fat separation. Undersampling was applied in the k-space and in the chemical shift encoding dimension to reduce the total scanning time. The method can reconstruct high quality water and fat images in 2D and 3D applications from undersampled data. As an extension, multipeak fat spectral models were incorporated into the CS-WF reconstruction to improve the water-fat separation quality. In 3D MRI, reduction factors of above three can be achieved, thus fully compensating the additional time needed in three-echo water-fat imaging. The method is demonstrated on knee and abdominal in vivo data.
authors.affiliation: Institute for Signal Processing, University of Lübeck, Lübeck, Germany. doneva@isip.uni-luebeck.de
authors.forename: Mariya
authors.initials: M
authors.lastname: Doneva
authors.forename: Peter
authors.initials: P
authors.lastname: Börnert
authors.forename: Holger
authors.initials: H
authors.lastname: Eggers
authors.forename: Alfred
authors.initials: A
authors.lastname: Mertins
authors.forename: John
authors.initials: J
authors.lastname: Pauly
authors.forename: Michael
authors.initials: M
authors.lastname: Lustig
mesh_terms: D000005:Abdomen / Q000033:anatomy & histology*; D000273:Adipose Tissue / Q000033:anatomy & histology; D000465:Algorithms; D001834:Body Water; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional; D007717:Knee / Q000033:anatomy & histology*; D016018:Least-Squares Analysis; D008279:Magnetic Resonance Imaging / Q000379:methods*; D016012:Poisson Distribution; D012189:Retrospective Studies