期刊
MAGNETIC RESONANCE IN MEDICINE
卷 65, 期 5, 页码 1352-1357出版社
WILEY-BLACKWELL
DOI: 10.1002/mrm.22796
关键词
noise reduction; metallic implants; SEMAC; singular value decomposition
资金
- NTU
- MOE
- [NIH-R21-EB008190]
- [NIH-P41-RR009784]
Magnetic resonance imaging (MRI) near metallic implants is often hampered by severe metal artifacts. To obtain distortion-free MR images near metallic implants, SEMAC (Slice Encoding for Metal Artifact Correction) corrects metal artifacts via robust encoding of excited slices against metal-induced field inhomogeneities, followed by combining the data resolved from multiple SEMAC-encoded slices. However, as many of the resolved data elements only contain noise, SEMAC-corrected images can suffer from relatively low signal-to-noise ratio. Improving the signal-to-noise ratio of SEMAC-corrected images is essential to enable SEMAC in routine clinical studies. In this work, a new reconstruction procedure is proposed to reduce noise in SEMAC-corrected images. A singular value decomposition denoising step is first applied to suppress quadrature noise in multi-coil SEMAC-encoded slices. Subsequently, the singular value decomposition-denoised data are selectively included in the correction of through-plane distortions. The experimental results demonstrate that the proposed reconstruction procedure significantly improves the SNR without compromising the correction of metal artifacts. Magn Reson Med 65:1352-1357, 2011. (c) 2011 Wiley-Liss, Inc.
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