Slice encoding for metal artifact correction with noise reduction

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, 2011. © 2011 Wiley‐Liss, Inc.