Abstract: According to one aspect of the invention, there is provided a method of constructing an image of a sample from MRI data, the method comprising: i) selectively acquiring one or more sets of MRI data generated from driving signals created under a specific set of operation parameters; ii) deriving a matrix representative of the selective acquisition of the one or more sets of MRI data; iii) processing the selectively acquired MRI data with the matrix to obtain output data; and iv) synthesizing the output data to construct the image of the sample.

Abstract: According to one aspect of the invention, there is provided a method of constructing a diagnostic image of a sample from MRI data acquired while subjecting the sample to an inhomogeneous polarizing magnetic field, the method comprising the steps of: i) deriving an estimate of the spatial map of the inhomogeneous polarizing magnetic field; ii) acquiring the MRI data; iii) processing the estimate of the spatial map with the acquired MRI data to obtain an estimate of the diagnostic image; iv) calculating an acquired data error in response to the estimates of the spatial map and the diagnostic image; v) updating the estimate of the spatial map in response to the calculated error; and repeating the steps iii) to v) to improve the estimate of the spatial map of the earlier iteration and the estimate of the diagnostic image, wherein the repetition is stopped when the calculated error of the latest iteration reaches within a tolerance range and wherein the estimate of the diagnostic image from the latest iteration be

Abstract: According to one aspect of the invention, there is provided a method of constructing an image of a sample from MRI data, the method comprising: i) selectively acquiring one or more sets of MRI data generated from driving signals created under a specific set of operation parameters; ii) deriving a matrix representative of the selective acquisition of the one or more sets of MRI data; iii) processing the selectively acquired MRI data with the matrix to obtain output data; and iv) synthesizing the output data to construct the image of the sample.

Abstract: According to one aspect of the invention, there is provided a method of constructing a diagnostic image of a sample from MRI data acquired while subjecting the sample to an inhomogeneous polarizing magnetic field, the method comprising the steps of: i) deriving an estimate of the spatial map of the inhomogeneous polarizing magnetic field; ii) acquiring the MRI data; iii) processing the estimate of the spatial map with the acquired MRI data to obtain an estimate of the diagnostic image; iv) calculating an acquired data error in response to the estimates of the spatial map and the diagnostic image; v) updating the estimate of the spatial map in response to the calculated error; and repeating the steps iii) to v) to improve the estimate of the spatial map of the earlier iteration and the estimate of the diagnostic image, wherein the repetition is stopped when the calculated error of the latest iteration reaches within a tolerance range and wherein the estimate of the diagnostic image from the latest iteration be

Abstract: A system and method for rapid acquisition of MRI data at multiple points in time in an.

Abstract: A system and method for rapid acquisition of MRI data at multiple points in time in an.

Abstract: A fast and efficient method for reconstructing an image from undersampled, parallel MRI data sets acquired with non-Cartesian trajectories includes the calculation of unsampled k-space data from the acquired k-space data and sets of calculated reconstruction coefficients. To reduce the computation time, only a few reference reconstruction coefficients are calculated using a matrix inversion step and the remaining reconstruction coefficients are produced by interpolating between the reference reconstruction coefficients.

Abstract: A 3D projection reconstruction pulse sequence is employed during a CEMRA dynamic study to acquire a time course series of k-space data sets. Signals from non-vascular voxels are suppressed by reconstructing a corresponding series of low resolution images using the centers of the acquired k-space data sets, and measuring the degree to which the signal behavior of voxels therein differ from a model of unwanted signal. Signals from voxels which do not differ from the model are suppressed and the resulting filtered low resolution images are transformed back to k-space and combined with the originally acquired peripheral k-space data to form complete, filtered k-space data sets from which images may be reconstructed.

Abstract: A method for reconstructing an image from undersampled, parallel MRI data sets acquired with a pulse sequence that samples k-space along radial trajectories includes the synthesis of training k-space data from the acquired data. The training k-space data is produced by reconstructing training images from the fully sampled, central k-space region of the acquired MRI data sets, and the training k-space data is used in a radial GRAPPA image reconstruction method to produce an image frame.

Abstract: A fast and efficient method for reconstructing an image from undersampled, parallel MRI data sets acquired with non-Cartesian trajectories includes the calculation of unsampled k-space data from the acquired k-space data and sets of calculated reconstruction coefficients. To reduce the computation time, only a few reference reconstruction coefficients are calculated using a matrix inversion step and the remaining reconstruction coefficients are produced by interpolating between the reference reconstruction coefficients.

Abstract: A method for reconstructing an image from undersampled, parallel MRI data sets acquired with a pulse sequence that samples k-space along radial trajectories includes the synthesis of training k-space data from the acquired data. The training k-space data is produced by reconstructing training images from the fully sampled, central k-space region of the acquired MRI data sets, and the training k-space data is used in a radial GRAPPA image reconstruction method to produce an image frame.

Abstract: A 3D projection reconstruction pulse sequence is employed during a CEMRA dynamic study to acquire a time course series of k-space data sets. Signals from non-vascular voxels are suppressed by reconstructing a corresponding series of low resolution images using the centers of the acquired k-space data sets, and measuring the degree to which the signal behavior of voxels therein differ from a model of unwanted signal. Signals from voxels which do not differ from the model are suppressed and the resulting filtered low resolution images are transformed back to k-space and combined with the originally acquired peripheral k-space data to form complete, filtered k-space data sets from which images may be reconstructed.