Maximum likelihood reconstruction for magnetic resonance fingerprinting

Bo Zhao, Fan Lam, Berkin Bilgic, Huihui Ye, Kawin Setsompop

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In this paper, we introduce a statistical estimation framework for magnetic resonance fingerprinting (MRF), a recently proposed quantitative imaging paradigm. Within this framework, we present a maximum likelihood formulation to simultaneously estimate multiple parameter maps from highly undersampled, noisy k-space data. A novel iterative algorithm, based on variable splitting, the alternating direction method of multipliers, and the variable projection method, is proposed to solve the resulting optimization problem. Representative results demonstrate that compared to the conventional MRF reconstruction, the proposed method yields improved accuracy and/or reduced acquisition time. Moreover, the proposed formulation enables theoretical analysis of MRF. For example, we show that with the gridding reconstruction as an initialization, the first iteration of the proposed method exactly produces the conventional MRF reconstruction.

Original languageEnglish (US)
Title of host publication2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015
PublisherIEEE Computer Society
Number of pages5
ISBN (Electronic)9781479923748
StatePublished - Jul 21 2015
Event12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 - Brooklyn, United States
Duration: Apr 16 2015Apr 19 2015

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452


Other12th IEEE International Symposium on Biomedical Imaging, ISBI 2015
Country/TerritoryUnited States


  • Magnetic resonance fingerprinting
  • alternating direction method of multiplier
  • iterative reconstruction
  • maximum likelihood estimation
  • variable projection
  • variable splitting

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging


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