TRADITIONAL POSTER - ismrm

Poster Sessions
3075. Background Phase Correction Using K-Space Filters in Phase Contrast Velocity Encoded MRI
Martin Uppman 1 , Michael Markl 2 , Bruce S. Spottiswoode 3,4
1 Lund Institute of Technology, Lund, Sweden; 2 Diagnostic Radiology, Medical Physics, Albert-Ludwigs Universität, Freiburg,
Germany; 3 MRC/UCT Medical Imaging Research Unit, Department of Human Biology, University of Cape Town, South Africa;
4 Department of Radiology, Stellenbosch University, South Africa
This work evaluates k-space high-pass filtering as a post-processing background phase correction technique for 2D phase contrast velocity encoded MRI.
Results are compared to an established technique which involves estimating the phase variation in stationary tissue and subtracting a fitted polynomial
surface. Phantom and in-vivo studies show that k-space filtering with a large kernel performs equally as well as a high order polynomial surface subtraction.
3076. Intrinsic Detection of Corrupted Data
Jason K. Mendes 1 , Dennis L. Parker 1
1 UCAIR, University of Utah, Salt Lake CIty, UT, United States
Correlations between adjacent K-Space lines can be used to detect non-rigid body motion or motion that occurs out of plane. The cross correlation between
two adjacent sets of equally spaced K-Space lines is a set of equally spaced delta functions convolved with an error function. The error function is a result of
correlation errors between adjacent sets of lines. These errors are present even when there is no motion of any kind, however, as the amount of data
corruption increases the error function broadens. As a result, a measure of the relative sharpness of the error function provides a measure of data corruption.
3077. SPI Motion Correction Using In-Plane Estimates
Ryan Keith Robison 1 , Kenneth Otho Johnson 1 , James Grant Pipe 1
1 Keller Center for Imaging Innovation, Barrow Neurological Institute, Phoenix, AZ, United States
Spiral Projection Imaging (SPI) allows for intrinsic estimation of rigid-body patient motion through the comparison of data between spiral planes that
correspond to different time points but similar k-space locations. The in-plane estimation scheme produces 2D estimates of motion for each spiral plane. Full
3D motion estimates can be obtained for each plane by combining the 2D estimates of spatially orthogonal, sequential triplets of spiral planes. In-vivo
images and quantitative estimation results are presented for simulated and in-vivo motion affected data.
3078. Reconstruction Exploiting Phase-Correlation Motion Estimation and Motion Compensation Methods
for Cine Cardiac Imaging
Mei-Lan Chu 1 , Jia-Shuo Hsu 1 , Hsiao-Wen Chung 1
1 Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
Motion estimation (ME) and motion compensation (MC) are successfully exploited by dynamic MRI as baseline estimation for enhancing reconstruction.
However, ME and MC have not been exploited as a standalone approach for direct dynamic MRI reconstruction, since the absence of full-resolution frames.
A robust reconstruction technique was proposed in this work to address this issue, based solely on phase-correlation ME and MC methods without
incorporating extra reconstruction routine. Cine cardiac images are tested with the proposed method, and the results indicate that the proposed method can
achieve improved temporal resolution even from substantially down-sampled k-space data.
Image Correction: Gradients & Frequency
Hall B Wednesday 13:30-15:30
3079. Compressive Slice Encoding for Metal Artifact Correction
Wenmiao Lu 1 , Kim Butts Pauly 2 , Garry Evan Gold 2 , John Mark Pauly 3 , Brian Andrew Hargreaves 2
1 Electrical & Electronic Engr., Nanyang Tech. University, Singapore, Singapore; 2 Radiology, Stanford University, Stanford, CA,
United States; 3 Electrical Engr., Stanford University, Stanford, CA, United States
Metal artifacts in MRI can be completely corrected by Slice Encoding for Metal Artifact Correction (SEMAC), which nonetheless incurs prolonged scan
times due to the additional phase encoding along slice-select direction. Here we incorporate SEMAC with compressed sensing to vastly reduce the number
of phase encoding steps required to resolve metal artifacts. The new technique, referred to as Compressive SEMAC, can greatly reduce scan times, while
producing high-quality distortion correction and SNR comparable to SEMAC with full sampling.
3080. Noise Reduction in Slice Encoding for Metal Artifact Correction Using Singular Value Decomposition
Wenmiao Lu 1 , Kim Butts Pauly 2 , Garry Evan Gold 2 , John Mark Pauly 3 , Brian Andrew Hargreaves 2
1 Electrical & Electronic Engr., Nanyang Tech. University, Singapore, Singapore; 2 Radiology, Stanford University, Stanford, CA,
United States; 3 Electrical 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.