Abstract: A variable density Cartesian sampling method that allows retrospective adjustment of temporal resolution, providing added flexibility for real-time applications where optimal temporal resolution may not be known in advance. The methods provide for a computationally efficient sampling methods where a first step includes producing a uniformly random sampling pattern using a golden ratio on a grid, and the second step is applying a nonlinear stretching operation to create a variable density sampling pattern. Diagnostic quality images may be recovered at different temporal resolutions.

Abstract: In some aspects, the present disclosure relates to a method for non-invasively assessing a myocardial region of a subject by computed tomography (CT). In one embodiment, the method comprises: acquiring non-contrast imaging data for a myocardial region of a subject using dual energy computed tomography (DECT) scanning; reconstructing, from the acquired non-contrast imaging data, monochromatic images for a plurality of energy levels in a range of energy levels; determining, based at least in part on the image reconstruction, attenuation values for each respective energy level of the plurality of energy levels; and performing at least one of detection and quantification of myocardial fibrosis based at least in part on differences in the attenuation values across the plurality of energy levels.

Abstract: A variable density Cartesian sampling method that allows retrospective adjustment of temporal resolution, providing added flexibility for real-time applications where optimal temporal resolution may not be known in advance. The methods provide for a computationally efficient sampling methods where a first step includes producing a uniformly random sampling pattern using a golden ratio on a grid, and the second step is applying a nonlinear stretching operation to create a variable density sampling pattern. Diagnostic quality images may be recovered at different temporal resolutions.

Abstract: Disclosed is a method for determining, among other things, the temperature profile of a medical implant in a patient when subjected to an MRI scan or machine, thus enabling a determination of the risk of temperature induced tissue necrosis or damage to the implant. The specific position of the implant in the patient changes the temperature dispersion in the body and is accounted for in the creation of the temperature profile. The method includes mapping with an imaging unit location, size and orientation of the medical implant in a patient, and storing the location, size and orientation in a mapped data. Then, translating the data to a model patient of gender, age, weight, height, and body structure of the patient with a model medical implant. Further, determining the parameters of an MRI unit to be used and computing the temperature profile of the implant to ascertain temperature impact.

Abstract: In some aspects, the present disclosure relates to a method for non-invasively assessing a myocardial region of a subject by computed tomography (CT). In one embodiment, the method comprises: acquiring non-contrast imaging data for a myocardial region of a subject using dual energy computed tomography (DECT) scanning; reconstructing, from the acquired non-contrast imaging data, monochromatic images for a plurality of energy levels in a range of energy levels; determining, based at least in part on the image reconstruction, attenuation values for each respective energy level of the plurality of energy levels; and performing at least one of detection and quantification of myocardial fibrosis based at least in part on differences in the attenuation values across the plurality of energy levels.

Abstract: A method for improving the signal-to-noise ratio (SNR) of TGRAPPA. The SNR of the ACS lines is proportional to the condition number of the GRAPPA kernel encoding equations. Therefore, the GRAPPA kernel estimated from higher SNR ACS lines amplifies the random noise in GRAPPA reconstruction. In TGRAPPA reconstruction of dynamic image series, a widely used method to acquire ACS lines is to average-all-frame (AAF). The present disclosure utilizes a tile-all-frame (TAF) as ACS lines to improve the SNR of the reconstructed images.

Abstract: A novel free-breathing myocardial T2* mapping combining multiple single-shot black-blood GRE-EPI images with automatic non-rigid motion correction. The present disclosure describes a method of accurate myocardial T2* measurements that is insensitive to respiratory motion, and is likely to reduce sensitivity to arrhythmia as well since each image is acquired in a single heart beat. The T2*-weighted GRE-EPI images are motion corrected using, e.g., automatic non-rigid motion correction to reduce mis-registration due to respiratory motion. A T2* map is calculated using the motion-corrected T2*-weighted images by fitting pixel intensities to a, e.g., two-parameter mono-exponential model.

Abstract: Parallel magnetic resonance imaging (pMRI) reconstruction techniques are commonly used to reduce scan time by undersampling the k-space data. In GRAPPA, a k-space based pMRI technique, the missing k-space data are estimated by solving a set of linear equations; however, this set of equations does not take advantage of the correlations within the missing k-space data. All k-space data in a neighborhood acquired from a phased-array coil are correlated. The correlation can be estimated easily as a self-constraint condition, and formulated as an extra set of linear equations to improve the performance of GRAPPA. We propose a modified k-space based pMRI technique call self-constraint GRAPPA (SC-GRAPPA) which combines the linear equations of GRAPPA with these extra equations to solve for the missing k-space data. Since SC-GRAPPA utilizes a least-squares solution of the linear equations, it has a closed-form solution that does not require an iterative solver.

Abstract: A method for improving the signal-to-noise ratio (SNR) of TGRAPPA. The SNR of the ACS lines is proportional to the condition number of the GRAPPA kernel encoding equations. Therefore, the GRAPPA kernel estimated from higher SNR ACS lines amplifies the random noise in GRAPPA reconstruction. In TGRAPPA reconstruction of dynamic image series, a widely used method to acquire ACS lines is to average-all-frame (AAF). The present disclosure utilizes a tile-all-frame (TAF) as ACS lines to improve the SNR of the reconstructed images.

Abstract: A novel free-breathing myocardial T2* mapping combining multiple single-shot black-blood GRE-EPI images with automatic non-rigid motion correction. The present disclosure describes a method of accurate myocardial T2* measurements that is insensitive to respiratory motion, and is likely to reduce sensitivity to arrhythmia as well since each image is acquired in a single heart beat. The T2*-weighted GRE-EPI images are motion corrected using, e.g., automatic non-rigid motion correction to reduce mis-registration due to respiratory motion. A T2* map is calculated using the motion-corrected T2*-weighted images by fitting pixel intensities to a, e.g., two-parameter mono-exponential model.

Abstract: A method for improving the signal-to-noise ratio (SNR) of TGRAPPA. The SNR of the ACS lines is proportional to the condition number of the GRAPPA kernel encoding equations. Therefore, the GRAPPA kernel estimated from higher SNR ACS lines amplifies the random noise in GRAPPA reconstruction. In TGRAPPA reconstruction of dynamic image series, a widely used method to acquire ACS lines is to average-all-frame (AAF). The present disclosure utilizes a tile-all-frame (TAF) as ACS lines to improve the SNR of the reconstructed images.

Abstract: A method for improving the signal-to-noise ratio (SNR) of TGRAPPA. The SNR of the ACS lines is proportional to the condition number of the GRAPPA kernel encoding equations. Therefore, the GRAPPA kernel estimated from higher SNR ACS lines amplifies the random noise in GRAPPA reconstruction. In TGRAPPA reconstruction of dynamic image series, a widely used method to acquire ACS lines is to average-all-frame (AAF). The present disclosure utilizes a tile-all-frame (TAF) as ACS lines to improve the SNR of the reconstructed images.

Abstract: Parallel magnetic resonance imaging (pMRI) reconstruction techniques are commonly used to reduce scan time by undersampling the k-space data. In GRAPPA, a k-space based pMRI technique, the missing k-space data are estimated by solving a set of linear equations; however, this set of equations does not take advantage of the correlations within the missing k-space data. All k-space data in a neighborhood acquired from a phased-array coil are correlated. The correlation can be estimated easily as a self-constraint condition, and formulated as an extra set of linear equations to improve the performance of GRAPPA. We propose a modified k-space based pMRI technique call self-constraint GRAPPA (SC-GRAPPA) which combines the linear equations of GRAPPA with these extra equations to solve for the missing k-space data. Since SC-GRAPPA utilizes a least-squares solution of the linear equations, it has a closed-form solution that does not require an iterative solver.

Abstract: In a method and magnetic resonance imaging apparatus wherein magnetic resonance signals are simultaneously received from an examination subject by multiple reception coils, a single, uninterrupted pulse sequence is executed which includes reference scans of the subject with a first sequence kernel that is optimized for coil sensitivity calibration, immediately followed by a series of accelerated image scans with a second sequence kernel, different from the first sequence kernel, that is optimized for imaging. Coil sensitivity maps for the respective coils are calculated from the data acquired in the reference scans, and an image of the subject is reconstructed by operating on the image data with a parallel reconstruction algorithm employing the calculated coil sensitivity maps.

Abstract: In a method and apparatus for generating a magnetic resonance image, raw magnetic resonance data are acquired from a subject for each of a number of PROPELLER strips using, for each strip, multiple magnetic resonance reception coils in a partial acquisition technique (PAT), and the raw data in said PROPELLER strips are entered into k-space according to the PROPELLER scan. A PAT reconstruction of the data in k-space is conducted dependent on the respective sensitivities of the reception coils, and a PROPELLER reconstruction of the data in k-space is conducted after the PAT reconstruction for generating a magnetic resonance image of the subject.

Abstract: In a method and apparatus for generating a magnetic resonance image, raw magnetic resonance data are acquired from a subject for each of a number of PROPELLER strips using, for each strip, multiple magnetic resonance reception coils in a partial acquisition technique (PAT), and the raw data in said PROPELLER strips are entered into k-space according to the PROPELLER scan. A PAT reconstruction of the data in k-space is conducted dependent on the respective sensitivities of the reception coils, and a PROPELLER reconstruction of the data in k-space is conducted after the PAT reconstruction for generating a magnetic resonance image of the subject.

Abstract: In a method and magnetic resonance imaging apparatus wherein magnetic resonance signals are simultaneously received from an examination subject by multiple reception coils, a single, uninterrupted pulse sequence is executed which includes reference scans of the subject with a first sequence kernel that is optimized for coil sensitivity calibration, immediately followed by a series of accelerated image scans with a second sequence kernel, different from the first sequence kernel, that is optimized for imaging. Coil sensitivity maps for the respective coils are calculated from the data acquired in the reference scans, and an image of the subject is reconstructed by operating on the image data with a parallel reconstruction algorithm employing the calculated coil sensitivity maps.