Compressive Sensing MRI with Wavelet Tree Sparsity

@inproceedings{Chen2012CompressiveSM,
  title={Compressive Sensing MRI with Wavelet Tree Sparsity},
  author={Chen Chen and Junzhou Huang},
  booktitle={NIPS},
  year={2012}
}
In Compressive Sensing Magnetic Resonance Imaging (CS-MRI), one can reconstruct a MR image with good quality from only a small number of measurements. This can significantly reduce MR scanning time. According to structured sparsity theory, the measurements can be further reduced to O(K + log n) for tree-sparse data instead of O(K +K log n) for standard K-sparse data with length n. However, few of existing algorithms have utilized this for CS-MRI, while most of them model the problem with total… CONTINUE READING
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