Presentation | 2010-11-15 Compressive Sensing of MR Images Using FREBAS Transform Koji MIYABAYASHI, Satoshi ITO, Yoshifumi YAMADA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Recently, there has been an emerging interest to accelerate MRI through iterative reconstruction of undersampled data based on the metrics that promote image sparsity. Compressed sensing theory predicts that such methods may accurately reconstruct images from data sampled much below the Nyquist limit through minimization of L1 norms. If the image is not sparse, a spasifying transformation should be used to allow compressed sensing. We proposed a new compressed sensing scheme in which FREBAS transform is used for the sparsifying transform. FREBAS transform is a kind of multi-resolution analysis, which decompose input image into many down-scaled images having different frequency bandwidth. In this work we compare the FREBAS compressed sensing with standard compressed sensing. Experiments show that our method can achieve a reduction factor higher than the standard compressed sensing method. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | k-space / sampling theorem / fast imaging |
Paper # | MI2010-75 |
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Committee | MI |
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Conference Date | 2010/11/8(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Medical Imaging (MI) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Compressive Sensing of MR Images Using FREBAS Transform |
Sub Title (in English) | |
Keyword(1) | k-space |
Keyword(2) | sampling theorem |
Keyword(3) | fast imaging |
1st Author's Name | Koji MIYABAYASHI |
1st Author's Affiliation | Department of Information Systems Sciences, Utsunomiya University() |
2nd Author's Name | Satoshi ITO |
2nd Author's Affiliation | Department of Information Systems Sciences, Utsunomiya University |
3rd Author's Name | Yoshifumi YAMADA |
3rd Author's Affiliation | Utsunomiya University |
Date | 2010-11-15 |
Paper # | MI2010-75 |
Volume (vol) | vol.110 |
Number (no) | 280 |
Page | pp.pp.- |
#Pages | 5 |
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