The General Hospital Corporation

The Brigham and Women's Hospital, Inc.

William Scott Hoge

Jonathan R Polimeni

Yan Zhang

Kawin Setsompop

Kun Zhou

Uvo Hölscher

Misha E Kilmer

Yulin Chang

Systems and methods include conversion of a first frame of k-space data acquired using a first initial readout polarity to first hybrid (k, y)-space data, conversion of a second frame of k-space data acquired using a second initial readout polarity to second hybrid (k, y)-space data, determination of a relationship between phase difference and y-position based on phase differences between a plurality of pixels located at k=a of first hybrid (k, y)-space data and a plurality of pixels at k=b of second hybrid (k, y)-space data, where a and b are constants, modification of the second hybrid (k, y)-space data based on the relationship, conversion of the modified second hybrid (k, y)-space data to a modified second frame of k-space data, generation of two single-polarity readout k-space frames based on the first frame of k-space data and the modified second frame of k-space data, and correction of a third frame of EPI image data based on the two single-readout polarity k-space frames.

Phase correction for echo-planar imaging

A method and imaging system is provided that can control a magnetic gradient system and an RF system of an MRI system according to a calibration pulse sequence to acquire positive readout gradient (RO+) data and negative readout gradient (RO&#x2212;) data. The RO+ data and the RQ&#x2212; data are assembled to form complete image data sets for the RO+ data and the RQ&#x2122; data and the RO+ data and the RO&#x2212; data are combined to generate the calibration data that is ghost-corrected, substantially free of ghost artifacts, or having reduced ghost artifacts compared to traditionally-acquired calibration data. Reconstruction coefficients are derived from the calibration data. The magnetic gradient system and the RF system are controlled according to an imaging pulse sequence to acquire image data and the image data is reconstructed into an image of the subject using the reconstruction coefficients.

System and method for dual-kernel image reconstruction

Systems and methods for combined ghost artifact correction and parallel imaging reconstruction of simultaneous multislice ('SMS') magnetic resonance imaging ('MRI') data are provided. Dual-polarity training data are used to generate ghost-free slice data, which are used as target data in a reconstruction kernel training process. The training data are used as source data in the reconstruction kernel training. As a result, reconstruction kernels are computed, which can be used to reconstruct images from SMS data in which slice-specific ghosting artifacts are removed.

System and method for reconstructing ghost-free images from data acquired using simultaneous multislice magnetic resonance imaging

Reconstructing an image from MRI data provided by an MRI machine includes: selecting a system transformation based on the MRI machine; selecting a subspace based on the system transformation; and obtaining a solution vector that solves a minimization problem. The minimization problem is formulated on the subspace, based on the MRI data. The image is reconstructed from the solution vector and displayed.

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Watertown, MA, United States of America

William Scott Hoge