General Electric Company

Ge Precision Healthcare LLC

Martin Andreas Janich

Thomas Kwok-Fah Foo

Graeme Colin McKinnon

Florian Wiesinger

Ana Beatriz Solana Sanchez

Anja Christina Sophie Brau

Xucheng Zhu

Andrew James Coristine

Nicolas Hehn

Image reconstruction systems and methods include providing sensitivity maps for coils of a magnetic resonance imaging (MRI) system to a neural network. The systems and methods also include providing interleaved k-space data to the neural network, wherein the interleaved k-space data includes partial k-space data interleaved with zeros, or synthesized k-space data, to provide an extended field of view (FOV) different from a FOV utilized during acquisition of the partial k-space data, wherein the partial k-space data were obtained during a scan of a region of interest with the MRI system. The systems and methods further include outputting, from the neural network, a final reconstructed MR image based at least on the sensitivity maps and the interleaved k-space data, wherein the final reconstructed MR image includes the FOV utilized during the acquisition of the partial k-space data.

System and method for deep learning-based accelerated magnetic resonance imaging with extended field of view coil sensitivity calibration

Methods and systems to obtain and apply Tpreparatory radiofrequency (RF) pulse sequences for magnetic resonance imaging (MRI) are provided. The iterative methods may employ propagation of the magnetization state of the object being imaged and a comparison with a target magnetization state. The methods disclosed may be used to obtain MRI pulse sequences that may optimize Trelaxation contrast. The produced RF pulse sequences may be robust to effects from inhomogeneity of the magnetic fields or other environmental or physiological perturbations.

Magnetic resonance T2 preparatory pulses for magnetic field inhomogeneity robustness and contrast optimization

A system and method for cardiac magnetic resonance imaging (MRI) is disclosed that facilitates the phase sensitive reconstruction of inversion recovery magnetization prepared data with minimal scan time penalty by acquiring the phase reference data with low spatial resolution. The technique can be applied for the investigation of myocardial tissue characterization by acquiring 2D and/or 3D late Gadolinium enhancement (LGE) scans after the injection of a Gadolinium contrast agent. Regional areas of contrast accumulation in scarred myocardial tissue appear bright on these T-weighted images. As disclosed here the proposed technique for phase sensitive inversion recovery acquisition with low resolution phase reference is robust against changes in inversion time, change in Tdue to Gadolinium contrast washout, high signal-to-noise ratio, and low scan time penalty compared to magnitude LGE.

Time optimal phase sensitive inversion recovery reconstruction for magnetic resonance imaging

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Munich, Germany

Martin Andreas Janich