title: SMS-HSL: Simultaneous multislice aliasing separation exploiting hankel subspace learning.
abstract: To develop a novel, simultaneous multislice reconstruction method that exploits Hankel subspace learning (SMS-HSL) for aliasing separation in the slice direction.
  
  
  
  An SMS signal model with the Hankel-structured matrix was proposed. To efficiently suppress interslice leakage artifacts from a signal subspace perspective, a null space was learned from the reference data combined over all slices other than a slice of interest using singular value decomposition. Given the fact that the Hankel-structured matrix is rank-deficient while the magnitude between the reference and its estimate is similar in k-space, the SMS-HSL was reformulated as a constrained optimization problem with both low-rank and magnitude priors. SMS signals were projected onto a slice-specific subspace while undesired signals were eliminated using the null space operator. The simulations and experiments were performed with increasing multiband factors up to 6 using the SMS-HSL and the split slice-GRAPPA.
  
  
  
  Compared with the split slice-GRAPPA, the SMS-HSL shows superior performance in suppressing aliasing artifacts and noises at high multiband factors even with: insufficient reference signals, a small number of coils, and a short distance between aliasing voxels.
  
  
  
  We successfully demonstrated the effectiveness of the SMS-HSL over the split slice-GRAPPA for aliasing separation in the slice direction. Magn Reson Med 78:1392-1404, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
authors.affiliation: Biomedical Imaging and Engineering Lab, Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea.
authors.forename: Suhyung
authors.initials: S
authors.lastname: Park
authors.affiliation: Biomedical Imaging and Engineering Lab, Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea.
authors.forename: Jaeseok
authors.initials: J
authors.lastname: Park
mesh_terms: D001921:Brain / Q000000981:diagnostic imaging; D003198:Computer Simulation; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D000069550:Machine Learning; D008279:Magnetic Resonance Imaging / Q000379:methods*; D012815:Signal Processing, Computer-Assisted
keywords: Hankel matrix; low rank; magnetic resonance imaging; parallel imaging; simultaneous multislice