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Slice Encoding for Metal Artifact Correction With Noise Reduction MAGNETIC RESONANCE IN MEDICINE Lu, W., Pauly, K. B., Gold, G. E., Pauly, J. M., Hargreaves, B. A. 2011; 65 (5): 1352-1357

Abstract

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.

View details for DOI 10.1002/mrm.22796

View details for Web of Science ID 000289760800018

View details for PubMedID 21287596

View details for PubMedCentralID PMC3079010