16:30 |
0121.
|
Slab Profile Encoding for
Minimizing Venetian Blind Artifact in 3D Diffusion-Weighted
Multislab Acquisition
Anh Tu Van1, Murat Aksoy1,
Samantha J. Holdsworth1, Daniel Kopeinigg1,
Sjoerd B. Vos2, and Roland Bammer1
1Radiology, Stanford University, Palo Alto,
CA, United States, 2Image
Sciences Institute, University Medical Center Utrecht,
Utrecht, Utrecht, Netherlands
Three-dimensional high-resolution diffusion imaging is
feasible in terms of scan time when multislab
acquisition is used. However, the main challenge of
multislab acquisitions is the slab boundary artifacts
caused by an imperfect slab-selective profile along the
slice dimension. By reconstructing all the slab
collectively using a SENSE-like method with the slab
excitation profiles as the “sensitivity maps,” the slab
boundary artifacts can be mitigated.
|
16:42 |
0122. |
Accelerated Parallel
Traveling Wave MR and Compressed Sensing Using a 2-Channel
Transceiver Array
Maryam Vareth1,2, Anita Flynn3,
Wei Bian1,2, Ye Li1, Daniel B.
Vigneron1,2, Sarah J. Nelson1,2,
and Xiaoliang Zhang1,2
1Radiology and Biomedical Imaging, UC San
Francisco, San Francisco, CA, United States, 2UC
Berkeley/UCSF Joint Graduate Group in Bioengineering,
San Francisco, CA, United States, 3EECS,
UC Berkeley, Berkeley, CA, United States
Parallel imaging and compressed sensing for traveling
wave MR is achievable with a very simple orthogonal
microstrip-resonator antenna geometry. We present
experimental results with three known undersampling
reconstruction algorithms (GRAPPA, SPIRiT andL1-SPIRiT)
at an acceleration factor of 1.8.
|
16:54 |
0123. |
Separation of Two
Simultaneously Encoded Slices with a Single Coil
Daniel B. Rowe1,2, Andrew S. Nencka2,
Andrzej Jesmanowicz2, and James S. Hyde2
1Department of Mathematics, Statistics, and
Computer Science, Marquette University, Milwaukee, WI,
United States, 2Department
of Biophysics, Medical College of Wisconsin, Milwaukee,
WI, United States
Two MR image slices are simultaneously encoded and a
single complex-valued aliased image is measured. From
the single complex-valued image, the previously
published magnitude-only and the current complex-valued
image separation methods are applied. It is shown that
the magnitude-only method can have challenges when the
difference in phase of the reference images is close to
zero. The complex-valued method works extremely well.
Reconstructing complex-valued images are important for
implementing complex-valued fMRI activation methods. The
reconstruction of simultaneously acquired slices
alleviates the necessity for slice timing correction and
voxels in different slices are temporally aligned to
produce proper connectivity maps.
|
17:06 |
0124.
|
Local Resolution Adaptation
for Curved Slice Imaging
Hans Weber1, Gerrit Schultz1,
Daniel Gallichan2, Jürgen Hennig1,
and Maxim Zaitsev1
1Department of Radiology, Medical Physics,
University Medical Center Freiburg, Freiburg, Germany, 2LIFMET,
Ecole Polytéchnique Fédérale de Lausanne, Lausanne,
Switzerland
The application of nonlinear spatial encoding magnetic
fields for both excitation and geometrically matched
encoding allows the acquisition of curved slices with
adjustable shape and thus increases the flexibility of
MRI. However, both spatially varying slice thickness and
in-plane resolution resulting from the nonlinearity of
the fields is an unwanted side effect for most
applications. The purpose of this study is to reduce the
spatial variation of the voxel sizes. This is obtained
by applying a concept for alias-free undersampling
previously developed for PatLoc imaging.
|
17:18 |
0125.
|
Simultaneous Multi-Slice
Flyback Echo Planar Imaging with Auto-Calibration
Kangrong Zhu1, Adam Kerr1, and
John M. Pauly1
1Stanford University, Stanford, California,
United States
The Blipped-CAIPI technique performs simultaneous
multi-slice EPI acquisition with reduced g-factor
penalty, but usually requires external calibration scans
for image reconstruction. In this work, a data
acquisition scheme which does not need any external
calibration scans is designed for simultaneous
multi-slice EPI and is demonstrated in in vivo brain
imaging. The internal auto-calibration in the proposed
method minimizes the image artifacts introduced by the
mismatch between the calibration data and the
accelerated data. The reconstructed images of the
proposed method can have higher SNR than the Blipped-CAIPI
method if the internal auto-calibration signal is
included in the final images.
|
17:30 |
0126.
|
Automated Selection of
2D-CAIPIRINHA Kernels and Application to 3D CE-MRA
Paul T. Weavers1, Eric A. Borisch1,
and Stephen J. Riederer1
1MR Research Laboratory, Mayo Clinic,
Rochester, Minnesota, United States
2D-CAIPIRINHA has been shown to reduce noise
amplification when compared to traditional 2D-SENSE.
However at high acceleration (R≥8) it is not clear which
kernel will best accomplish this. An automated method to
select the optimal kernel in a receiver coil and
patient-specific manner in less than ten seconds has
been developed. It has been validated with a
retrospective study of nine sets of 3D foot exams, as
well as in a prospective 3D contrast-enhanced MRA study.
|
17:42 |
0127.
|
ESPIRiT Reconstruction
Using Soft SENSE
Martin Uecker1, Patrick Virtue1,
Shreyas S. Vasanawala2, and Michael Lustig1
1Electrical Engineering and Computer
Sciences, University of California, Berkeley, Berkeley,
California, United States, 2Department
of Radiology, Stanford University, Stanford, California,
United States
Recently, a new technique to estimate sensitivity maps
from the calibration data has been proposed (ESPIRiT).
In the ideal case, this technique yields a single set of
sensitivity maps, which can be used with SENSE. With
data corruption, multiple sets of maps naturally appear
when using this method. They correspond to additional
signal components which are implicitly taken into
account in SPIRiT (and GRAPPA), but do not fit the SENSE
model using a single set of maps. Here, we propose “soft
SENSE”, which uses multiple weighted sets of maps and
has similar properties as SPIRiT.
|
17:54 |
0128. |
Improving K-T
Auto-Calibrating Parallel Imaging for 3D Cardiac Cine MRI
Using Prior-Reconstruction Static Tissue Estimation and
Elimination
Peng Lai1, Shreyas S. Vasanawala2,
Atsushi Nozaki3, Maggie Fung4, and
Anja C.S Brau5
1MR Applications & Workflow, GE Healthcare,
Menlo Park, CA, United States, 2Radiology,
Stanford University, Stanford, CA, United States, 3MR
Applications & Workflow, GE Healthcare, Asahigaoka,
Hino, Japan, 4MR
Applications & Workflow, GE Healthcare, Jersey City, NJ,
United States, 5MR
Applications & Workflow, GE Healthcare, Garching,
Munchen, Germany
High acceleration needed for 3D cine MRI potentially
results in residual artifacts. High density coils and
k-t acceleration methods demand long reconstruction
time. In this work, we developed a method that
automatically estimates and eliminates static tissue
signals from k-t accelerated 3D cine datasets. This
method enables k-t reconstruction on dynamic tissue
signals with reduced aliasing and furthermore enables
selective reconstruction on locations and coil channels
around the heart only. Based on our evaluations, the
proposed method can improve 3D cardiac cine MRI in both
image quality and computation efficiency.
|
18:06 |
0129.
|
Iterative Trajectory
Correction for Radial Projection Imaging
Tobias Wech1, Johannes Tran-Gia1,
Dietbert Hahn1, and Herbert Köstler1
1Institute of Radiology, University of
Würzburg, Würzburg, Germany
Eddy currents as well as gradient delays lead to
deviations in measured trajectories. Especially in
non-Cartesian imaging, these errors can cause severe
image artifacts. In this work, we propose a method which
allows for a correction of trajectory errors for radial
projection imaging with no need of any separately
acquired calibration data. The method iteratively
translates the measured projections using the GRAPPA
operator in order to maximize the self-consistency of
data in oversampled k-space regions. This results in
shifted coordinates representing the truly measured
trajectory.
|
18:18 |
0130.
|
Calibrationless Chemical
Shift Encoded Imaging Using a Time-Segmented K-Space
Reconstruction
Samir D. Sharma1,2, Joshua D. Trzasko3,
and Armando Manduca3
1Radiology, University of Wisconsin -
Madison, Madison, WI, United States, 2Electrical
Engineering, University of Southern California, Los
Angeles, CA, United States, 3Mayo
Clinic, Rochester, Minnesota, United States
Conventional image-domain-based methods for chemical
shift encoding are limited both by their long scan time,
which can restrict spatial resolution and/or volume
coverage, and their sensitivity to intraecho
off-resonance, which can cause geometric distortion.
Previous works have proposed either accelerating
image-domain-based methods or using a k-space-based
formulation to mitigate the effects of intraecho
off-resonance. In this work, we develop and demonstrate
a framework for accelerated k-space-based chemical shift
encoding. We employ a time-segmented approximation of
the multispecies MR signal equation and we exploit prior
information on intercoil structure and image sparsity to
achieve acceleration. We demonstrate accelerated
water-fat separation with reduced geometric distortions
as compared to a conventional image-domain-based method.
|
|