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Magnetic resonance fingerprinting review part 2: Technique and directions.
McGivney, Debra F; Boyacioglu, Rasim; Jiang, Yun; Poorman, Megan E; Seiberlich, Nicole; Gulani, Vikas; Keenan, Kathryn E; Griswold, Mark A; Ma, Dan.
Affiliation
  • McGivney DF; Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA.
  • Boyacioglu R; Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA.
  • Jiang Y; Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA.
  • Poorman ME; Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA.
  • Seiberlich N; Department of Physics, University of Colorado Boulder, Boulder, Colorado, USA.
  • Gulani V; Physical Measurement Laboratory, National Institute of Standards and Technology, Boulder, Colorado, USA.
  • Keenan KE; Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.
  • Griswold MA; Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA.
  • Ma D; Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA.
J Magn Reson Imaging ; 51(4): 993-1007, 2020 04.
Article in En | MEDLINE | ID: mdl-31347226
ABSTRACT
Magnetic resonance fingerprinting (MRF) is a general framework to quantify multiple MR-sensitive tissue properties with a single acquisition. There have been numerous advances in MRF in the years since its inception. In this work we highlight some of the recent technical developments in MRF, focusing on sequence optimization, modifications for reconstruction and pattern matching, new methods for partial volume analysis, and applications of machine and deep learning. Level of Evidence 2 Technical Efficacy Stage 2 J. Magn. Reson. Imaging 2020;51993-1007.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Magnetic Resonance Imaging Language: En Journal: J Magn Reson Imaging Journal subject: DIAGNOSTICO POR IMAGEM Year: 2020 Document type: Article Affiliation country: United States
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Magnetic Resonance Imaging Language: En Journal: J Magn Reson Imaging Journal subject: DIAGNOSTICO POR IMAGEM Year: 2020 Document type: Article Affiliation country: United States