Fast Multiclass Dictionaries Learning With Geometrical Directions in MRI Reconstruction

  title={Fast Multiclass Dictionaries Learning With Geometrical Directions in MRI Reconstruction},
  author={Zhifang Zhan and Jian-Feng Cai and Di Guo and Yunsong Liu and Zhong Chen and Xiaobo Qu},
  journal={IEEE Transactions on Biomedical Engineering},
Objective: Improve the reconstructed image with fast and multiclass dictionaries learning when magnetic resonance imaging is accelerated by undersampling the k-space data. Methods: A fast orthogonal dictionary learning method is introduced into magnetic resonance image reconstruction to provide adaptive sparse representation of images. To enhance the sparsity, image is divided into classified patches according to the same geometrical direction and dictionary is trained within each class. A new… CONTINUE READING
Recent Discussions
This paper has been referenced on Twitter 5 times over the past 90 days. VIEW TWEETS


Publications citing this paper.
Showing 1-10 of 31 extracted citations


Publications referenced by this paper.
Showing 1-10 of 58 references

Magnetic resonance image reconstruction from undersampled measurements using a patch-based nonlocal operator

  • X. Qu
  • Med. Image Anal., vol. 18, pp. 843–856, Aug. 2014…
  • 2014
Highly Influential
9 Excerpts

Magnetic resonance image reconstruction using trained geometric directions in 2D redundant wavelets domain and non-convex optimization

  • B. Ning
  • Magn. Reson. Imag., vol. 31, pp. 1611–1622, Nov…
  • 2013
Highly Influential
11 Excerpts

Distributed optimization and statistical learning via the alternating direction method of multipliers

  • S. Boyd
  • Found. Trends Mach. Learn., vol. 3, pp. 1–122…
  • 2011
Highly Influential
7 Excerpts

Similar Papers

Loading similar papers…