title: Fast group matching for MR fingerprinting reconstruction.
abstract: OBJECTIVE
  MR fingerprinting (MRF) is a technique for quantitative tissue mapping using pseudorandom measurements. To estimate tissue properties such as T1 , T2 , proton density, and B0 , the rapidly acquired data are compared against a large dictionary of Bloch simulations. This matching process can be a very computationally demanding portion of MRF reconstruction.
  
  
  METHODS
  We introduce a fast group matching algorithm (GRM) that exploits inherent correlation within MRF dictionaries to create highly clustered groupings of the elements. During matching, a group specific signature is first used to remove poor matching possibilities. Group principal component analysis (PCA) is used to evaluate all remaining tissue types. In vivo 3 Tesla brain data were used to validate the accuracy of our approach.
  
  
  RESULTS
  For a trueFISP sequence with over 196,000 dictionary elements, 1000 MRF samples, and image matrix of 128 × 128, GRM was able to map MR parameters within 2s using standard vendor computational resources. This is an order of magnitude faster than global PCA and nearly two orders of magnitude faster than direct matching, with comparable accuracy (1-2% relative error).
  
  
  CONCLUSIONS
  The proposed GRM method is a highly efficient model reduction technique for MRF matching and should enable clinically relevant reconstruction accuracy and time on standard vendor computational resources.
authors.affiliation: Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.|Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA.
authors.forename: Stephen F
authors.initials: SF
authors.lastname: Cauley
authors.affiliation: Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.|Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA.
authors.forename: Kawin
authors.initials: K
authors.lastname: Setsompop
authors.affiliation: Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.
authors.forename: Dan
authors.initials: D
authors.lastname: Ma
authors.affiliation: Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.
authors.forename: Yun
authors.initials: Y
authors.lastname: Jiang
authors.affiliation: Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.|Department of Biomedical Engineering, Zhejiang University, Hangzhou, China.
authors.forename: Huihui
authors.initials: H
authors.lastname: Ye
authors.affiliation: Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.|Department of Electrical Engineering and Computer Science; Harvard-MIT Division of Health Sciences and Technology, Institute of Medical Engineering and Science, MIT, Cambridge, Massachusetts, USA.
authors.forename: Elfar
authors.initials: E
authors.lastname: Adalsteinsson
authors.affiliation: Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.|Department of Radiology, Case Western Reserve University and University Hospitals of Cleveland, Cleveland, Ohio, USA.
authors.forename: Mark A
authors.initials: MA
authors.lastname: Griswold
authors.affiliation: Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.|Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA.|Department of Electrical Engineering and Computer Science; Harvard-MIT Division of Health Sciences and Technology, Institute of Medical Engineering and Science, MIT, Cambridge, Massachusetts, USA.
authors.forename: Lawrence L
authors.initials: LL
authors.lastname: Wald
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology* / Q000502:physiology*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: MR fingerprinting; clustering; matching; pruning