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MRI image reconstruction via new K-space sampling scheme based on separable transform

Oliaiee, A ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.1109/IranianMVIP.2013.6779963
  3. Publisher: IEEE Computer Society , 2013
  4. Abstract:
  5. Reducing the time required for MRI, has taken a lot of attention since its inventions. Compressed sensing (CS) is a relatively new method used a lot to reduce the required time. Usage of ordinary compressed sensing in MRI imaging needs conversion of 2D MRI signal (image) to 1D signal by some techniques. This conversion of the signal from 2D to 1D results in heavy computational burden. In this paper, based on separable transforms, a method is proposed which enables the usage of CS in MRI directly in 2D case. By means of this method, imaging can be done faster and with less computational burden
  6. Keywords:
  7. 2D-Compressed Sensing ; 2D-SLO Algorithm ; Magnetic Resonance Imaging(MRI) ; Computer vision ; Image reconstruction ; Signal systems ; Wavelet transforms ; 1D signals ; Compressive sensing ; Computational burden ; K-space sampling ; Mri imaging ; Required time ; Sparsity
  8. Source: Iranian Conference on Machine Vision and Image Processing, MVIP ; September , 2013 , Pages 127-130 ; 21666776 (ISSN) ; 9781467361842 (ISBN)
  9. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6779963