Magnetic resonance fingerprinting review part 2: Technique and directions. Issue 4 (25th July 2019)

• Record Type: Journal Article
• Authors: McGivney, Debra F.; Boyacıoğlu, Rasim; Jiang, Yun; Poorman, Megan E.; Seiberlich, Nicole; Gulani, Vikas; Keenan, Kathryn E.; Griswold, Mark A.; Ma, Dan
• Is Part Of: Journal of magnetic resonance imaging. Volume 51:Issue 4(2020)
• Page Start: 993
• Page End: 1007
• Publication Date: 2019-07-25
• Subjects: magnetic resonance fingerprinting -- optimization -- reconstruction -- machine learning -- deep learning; Magnetic resonance imaging -- Periodicals; 616
• DOI: 10.1002/jmri.26877
• Languages: English
• ISSNs: 1053-1807

Abstract

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;51:993–1007.