Abstract #0576
k-t SPARKS: Dynamic Parallel MRI Exploiting Sparse Kalman Smoother
Suhyung Park 1 and Jaeseok Park 2
1
Center for Neuroscience Imaging Research,
Institute for Basic Science (IBS), Sungkyunkwan
University, Suwon, Gyeong Gi-Do, Korea,
2
Biomedical
Imaging and Engineering Lab., Department of Global
Biomedical Engineering, Sungkyunkwan University, Suwon,
Gyeong Gi-Do, Korea
Dynamic parallel magnetic resonance imaging (PMRI) has
been widely used in a variety of fast imaging
applications to accelerate the data acquisition without
any compromise of the spatial-temporal resolution. An
accurate calibration is the key for successful dynamic
PMRI. However, the calibration quality typically
decreases with both small amount of calibrating signals
and motion-induced temporally varying coil sensitivity.
In this work, we propose a new, dynamic PMRI exploiting
sparse Kalman smoother (k-t SPARKS) for robust
calibration and reconstruction in the presence of
time-varying coil sensitivity, in which the proposed
method incorporates the Kalman smoother calibration and
the sparse signal recovery into a single optimization
problem, leading to joint estimation of time-varying
convolution kernel and full k-space. Simulation and
experiments were performed using both the proposed and
conventional methods in the free-breathing cardiac cine
applications for comparison.
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