Literature DB >> 29681776

Quantification of relaxation times in MR Fingerprinting using deep learning.

Zhenghan Fang1, Yong Chen1, Weili Lin1, Dinggang Shen1.   

Abstract

MRF is a new quantitative MR imaging technique, which can provide rapid and simultaneous measurement of multiple tissue properties. Compared to the fast speed for data acquisition, the post-processing to extract tissue properties with MRF is relatively slow and often requires a large memory for the storage of both image dataset and MRF dictionary. In this study, a convolutional neural network was developed, which can provide rapid estimation of multiple tissue properties in 0.1 sec. The T1 and T2 values obtained in white matter and gray matter are also in a good agreement with the results from pattern matching.

Entities:  

Year:  2017        PMID: 29681776      PMCID: PMC5909960     

Source DB:  PubMed          Journal:  Proc Int Soc Magn Reson Med Sci Meet Exhib Int Soc Magn Reson Med Sci Meet Exhib        ISSN: 1524-6965


  1 in total

1.  Deep Learning for Magnetic Resonance Fingerprinting: A New Approach for Predicting Quantitative Parameter Values from Time Series.

Authors:  Elisabeth Hoppe; Gregor Körzdörfer; Tobias Würfl; Jens Wetzl; Felix Lugauer; Josef Pfeuffer; Andreas Maier
Journal:  Stud Health Technol Inform       Date:  2017
  1 in total

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