- Poster presentation
- Open Access
Distributed compressed sensing to accelerate cine cardiac MRI
© Zamani et al; licensee BioMed Central Ltd. 2015
- Published: 3 February 2015
- Discrete Wavelet Transform
- Compressed Sensing
- Temporal Estimation
- Sparse Reconstruction
- Compressed Sensing Theory
Compressed sensing (CS) is an efficient tool that accelerates the data acquisition in MRI through the significant reduction of required measurements for image reconstruction. In recent years, there have been significant interests in the use of Compressed Sensing (CS) in Dynamic applications . Since Cine cardiac images, as a dynamic data, has both spatial and temporal sparsity, it is a good candidate for CS with high acceleration factor .
We proposed a new method to highly accelerate Cine cardiac images using spatial and temporal sparsity based on CS theory. The proposed method high efficiency under-sampling rate and fidelity in CS theory. The results show the efficiency and accuracy of the proposed methods compared to other conventional CS methods. Concluding that proposed method outperforms other methods in both SNR and SSIM with 10% and 8%, respectively.
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