ELECTRONIC POSTER - ismrm

14:00 5068. Accelerated Point Spread Function Mapping Using Compressed Sensing for EPI
Geometric Distortion Correction
Iulius Dragonu 1 , Juergen Hennig 1 , Maxim Zaitsev 1
1 Diagnostic Radiology, University Hospital Freiburg, Freiburg, Baden Wuerttemberg, Germany
Single-shot echo-planar imaging (EPI) is a fast technique allowing the acquisition of an image following a single RF excitation. The
high temporal resolution of EPI makes it the method of choice for applications such as fMRI or diffusion tensor imaging. However,
EPI is prone to geometric and intensity distortions in the presence of magnetic field inhomogeneities. Several correction techniques
have been proposed in the past based on field map acquisitions or point spread function (PSF) acquisitions. Parallel imaging
techniques were employed for accelerating the PSF data acquisition. In this work we demonstrate that compressed sensing (CS)
reconstruction can be used for acquiring the PSF data set with high acceleration factors for accurate geometric distortion corrections.
14:30 5069. Distortion Correction for Echo Planar MR Imaging Using the Point Spread
Function (PSF) Map with Bregman Iteration
Yu Cai 1 , Weili Lin, Qingwei Liu, Craig Hamilton 2 , Hongyu An
1 Department of Radiology, University of North Carolina-Chapel Hill, Chapel Hill, NC, United States; 2 Wake
Forest University
Point Spread Function (PSF) mapping techniques have shown promise for geometric distortion correction in Echo Planar Imaging
(EPI)(1), where the distortion information is mapped by applying additional phase encoding gradients with a constant time (PSF
encoding). Cai et al(2) introduced the inverse solution of the PSF map with the Tikhonov regularization method for EPI distortion
correction. The smoothness penalty in the Tikhonov regularization causes it sensitive to the aliasing artifact in its reconstructed image
and fine textile structure blurring. Here we apply the total variation (TV) regularization with Bregman iteration method(3) to the PSF
map in which the penalty term is adaptively updated based on the Bregman distance, which is immune to the above effects. The
proposed approach compared with the Tikhonov regularization methods were evaluated at 3.0T with human subjects while at 9.4T
with rats.
15:00 5070. Improved PSF-Based EPI Distortion Correction in Human Imaging at 7 Tesla
Myung-Ho In 1 , Jun-Young Jung 2 , Se-Hong Oh 2 , Maxim Zaitsev 3 , Zang-Hee Cho 2 , Oliver
Speck 1
1 Department Biomedical Magnetic Resonance, Institute for Experimental Physics, Otto-von-Guericke
University Magdeburg, Magdeburg, Germany; 2 Neuroscience Research Institute, Gachon University of
Medicine and Science, Inchoen, Korea, Republic of; 3 Department of Radiologic Research, Medical Physics,
University Hospital Freiburg, Freiburg, Germany
This method proposes an improved method with which distortions in EPI images in the ultra high field MRI such as 7.0 Tesla can be
correct automatically and with high fidelity. The correction is a modification and extension of the point spread function (PSF) method
previously developed. In addition to more precise mapping and correction of blurring, the method removes flow induced artifacts
which can cause errors in the shift map derived from the PSF. The advantages of the proposed method for the correction of geometric
distortions in EPI are demonstrated in human brain in vivo at 7.0 Tesla.
Topics in Image Analysis
Hall B Monday 14:00-16:00 Computer 124
14:00 5071. Automated Analysis of ACR Phantom Data as an Adjunct to a Regular MR Quality
Assurance Program
Lawrence P. Panych 1,2 , Lisa Bussolari 1 , Robert V. Mulkern, 23
1 Radiology, Brigham and Women's Hospital, Boston, MA, United States; 2 Radiology, Harvard Medical School,
Boston, MA, United States; 3 Radiology, Children's Hospital, Boston, MA, United States
A Matlab-based package for automatic analysis of phantom images was developed. The package analyzes images of the American
College of Radiology (ACR) phantom, performing measurements similar to those required as part of the ACR accreditation program
along with other useful measures. Analysis of the data from five 1.5T MR systems acquired during weekly QA scans was performed.
Such data can be help to identify potential system problems, such as lower than usual SNR, and serve as an adjunct to a regular
program of quality assurance.
14:30 5072. Weisskoff Stability Metrics Dependence on K-Space Trajectory
E. Brian Welch 1,2 , Ad Moerland 3 , Elizabeth A. Moore 3 , J. Christopher Gatenby 1 , John C.
Gore 1
1 Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN,
United States; 2 MR Clinical Science, Philips Healthcare, Highland Heights, OH, United States; 3 MR Clinical
Science, Philips Healthcare, Best, Netherlands
Measurement of an MR scanner’s signal stability is important for clinical and research sites acquiring data known to be adversely
affected by system instabilities such as functional MRI. In particular, the Weisskoff plot and its associated radius of decorrelation
(RDC) metric are often used to compare systems. The RDC is known to be influenced by the noise level of the data. However, it has
not been widely reported that the observed RDC is also affected by k-space trajectory. Here we present stability measurements from a
single scanner collected using four distinct k-space acquisition trajectories: Cartesian, multivane (propeller), spiral and radial.