Wenmiao Lu1, Kim Butts Pauly2,
Garry Evan Gold2, John Mark Pauly3, Brian Andrew
Hargreaves2
1Electrical & Electronic Engr.,
Nanyang Tech. University, Singapore, Singapore; 2Radiology,
Stanford University, Stanford, CA, United States; 3Electrical
Engr., Stanford University, Stanford, CA, United States
To
obtain distortion-free MR images near metallic implants, SEMAC (slice
encoding for metal artifact correction) resolves metal artifacts with
additional z-phase encoding, and corrects metal artifacts by combining
multiple SEMAC-encoded slices. However, many of the resolved voxels contain
only noise rather than signals, which degrades signal-to-noise ratio (SNR) in
the corrected images. Here the SEMAC reconstruction is modified to perform
denoising using singular value decomposition, which exploits the redundancy
in the SEMAC-encoded data received from multiple coils. We demonstrate the efficacy
of the proposed technique in several important imaging scenarios where
SEMAC-corrected images are liable to relatively low SNR.