59 research outputs found
A plug-and-play synthetic data deep learning for undersampled magnetic resonance image reconstruction
Magnetic resonance imaging (MRI) plays an important role in modern medical
diagnostic but suffers from prolonged scan time. Current deep learning methods
for undersampled MRI reconstruction exhibit good performance in image
de-aliasing which can be tailored to the specific kspace undersampling
scenario. But it is very troublesome to configure different deep networks when
the sampling setting changes. In this work, we propose a deep plug-and-play
method for undersampled MRI reconstruction, which effectively adapts to
different sampling settings. Specifically, the image de-aliasing prior is first
learned by a deep denoiser trained to remove general white Gaussian noise from
synthetic data. Then the learned deep denoiser is plugged into an iterative
algorithm for image reconstruction. Results on in vivo data demonstrate that
the proposed method provides nice and robust accelerated image reconstruction
performance under different undersampling patterns and sampling rates, both
visually and quantitatively.Comment: 5 pages, 3 figure
Minimizing echo and repetition times in magnetic resonance imaging using a double half‐echo k‐space acquisition and low‐rank reconstruction
Sampling k-space asymmetrically (ie, partial Fourier sampling) in the readout direction is a common way to reduce the echo time (TE) during magnetic resonance image acquisitions. This technique requires overlap around the center of k-space to provide a calibration region for reconstruction, which limits the minimum fractional echo to ~60% before artifacts are observed. The present study describes a method for reconstructing images from exact half echoes using two separate acquisitions with reversed readout polarity, effectively providing a full line of k-space without additional data around central k-space. This approach can benefit sequences or applications that prioritize short TE, short inter-echo spacing or short repetition time. An example of the latter is demonstrated to reduce banding artifacts in balanced steady-state free precession
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