By Topic

Combined sparsifying transforms for compressed sensing MRI

Sign In

Full text access may be available.

To access full text, please use your member or institutional sign in.

Formats Non-Member Member
$33 $33
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
X. Qu ; Fujian Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, People's Republic of China ; X. Cao ; D. Guo ; C. Hu
more authors

In traditional compressed sensing MRI methods, single sparsifying transform limits the reconstruction quality because it cannot sparsely represent all types of image features. Based on the principle of basis pursuit, a method that combines sparsifying transforms to improve the sparsity of images is proposed. Simulation results demonstrate that the proposed method can well recover different types of image features and can be easily associated with total variation.

Published in:

Electronics Letters  (Volume:46 ,  Issue: 2 )