Abstract: A method, system and computer program product for obtaining first and second sets of image data generated by performing a series of MRI sequences using first and second different transmit RF parameters; calculating a correlation map from the first and second sets of image data; and correcting the first set of image data using the calculated correlation map to obtain a corrected image. Also disclosed is a method, system and computer program product for determining at least two transmit RF parameters by: obtaining spatially-resolved B1 amplitude measurements; performing at least two spatially-resolved analyses on the obtained spatially-resolved B1 amplitude measurements to obtain at least two sub-sets of spatially-resolved B1 amplitude measurements; determining at least two transmit RF parameters to be used in a series of MRI sequences based on the obtained at least two sub-sets of spatially-resolved B1 amplitude measurements; and storing the at least two transmit RF parameters.

Abstract: A method, system and computer program product for performing imagine processing including obtaining spatially-resolved B1 amplitude measurements obtained using at least one RF parameter; performing at least one spatially-resolved analysis on the obtained spatially-resolved B1 amplitude measurements; determining an updated value of the at least one RF parameter to be used in a series of MRI sequences based on the performed spatially-resolved analysis; and storing the updated value of the at least one RF parameter. The updated value of the at least one RF parameter can then be used to perform the series of MRI sequences.

Abstract: A method and system for modifying a series of magnetic resonance imaging (MRI) scan sequences for use in a single MRI examination. In one embodiment, a method and system intersperse a set of B1 amplitude measurement sequences within a received series of MRI scan sequences such that an RF parameter value of at least one scan sequence of the received series of MRI scan sequences is altered based on the results of at least one of the interspersed set of B1 amplitude measurement sequences.

Abstract: An apparatus for magnetic resonance imaging includes processing circuitry to obtain a set of sequence instructions for performing a magnetic resonance scan; partition the obtained set of sequence instructions into a plurality of kernels by determining partition time points defining boundaries of the plurality of kernels, wherein the partition time points are not equally spaced in time; convert a first kernel of the plurality of kernels into a first hardware instruction set; transmit the first hardware instruction set to a hardware board controller for execution; and reconstruct a magnetic resonance image from received data, including data obtained by executing the first kernel.

Abstract: A method for performing patient-specific B1 field shimming in a magnetic resonance imaging system includes obtaining patient information of a patient to be imaged by the magnetic resonance imaging system. The method further includes determining an orientation of a projection based on the obtained patient information. The method also includes acquiring B1 projection data, using the magnetic resonance imaging system, along the determined orientation of the projection. In addition, the method includes determining a set of B1 shimming parameters based on the acquired B1 projection data.

Abstract: An apparatus and method are provided to simultaneously provide good image quality and fast image reconstruction from magnetic resonance imaging (MRI) data by selecting an appropriate value for the regularization parameter used in compressed sensing (CS) image reconstruction. In CS reconstruction a high-resolution image can be reconstructed from randomized undersampled data by imposing sparsity in multi-scale transformation (e.g., wavelet) domain. Further, in the transformation domain, a threshold can be determined between signal and noise levels of the transform coefficients. A regularization parameter based on this threshold scales the regularization term, which imposes sparsity, relative to the data fidelity term in an objective function, thereby balancing the tradeoff between noise and smoothing.

Abstract: A method and apparatus are provided to perform controlled aliasing in parallel imaging (CAIPI) using time shifts between the radio frequency (RF) excitation pulses and the waveform of the slice-select gradient field to shift respective sampling points within the two-dimensions of k-space corresponding to phase encoding. Thus, a CAIPI sampling pattern is generated using time shifts, rather than by modulating the RF excitation pulses or gradient fields.

Abstract: A method and apparatus are provided to perform controlled aliasing in parallel imaging (CAIPI) using time shifts between the radio frequency (RF) excitation pulses and the waveform of the slice-select gradient field to shift respective sampling points within the two-dimensions of k-space corresponding to phase encoding. Thus, a CAIPI sampling pattern is generated using time shifts, rather than by modulating the RF excitation pulses or gradient fields.

Abstract: An apparatus and method are provided to simultaneously provide good image quality and fast image reconstruction from magnetic resonance imaging (MRI) data by selecting an appropriate value for the regularization parameter used in compressed sensing (CS) image reconstruction. In CS reconstruction a high-resolution image can be reconstructed from randomized undersampled data by imposing sparsity in multi-scale transformation (e.g., wavelet) domain. Further, in the transformation domain, a threshold can be determined between signal and noise levels of the transform coefficients. A regularization parameter based on this threshold scales the regularization term, which imposes sparsity, relative to the data fidelity term in an objective function, thereby balancing the tradeoff between noise and smoothing.

Abstract: An apparatus and method are provided to simultaneously provide good image quality and fast image reconstruction from magnetic resonance imaging (MRI) data by selecting an appropriate value for the regularization parameter used in compressed sensing (CS) image reconstruction. In CS reconstruction a high-resolution image can be reconstructed from randomized undersampled data by imposing sparsity in multi-scale transformation (e.g., wavelet) domain. Further, in the transformation domain, a threshold can be determined between signal and noise levels of the transform coefficients. A regularization parameter based on this threshold scales the regularization term, which imposes sparsity, relative to the data fidelity term in an objective function, thereby balancing the tradeoff between noise and smoothing.

Abstract: An apparatus and method of detecting a characteristic in an image is performed by obtaining, from an image capturing apparatus, raw signal data formed from a plurality of data samples and including a signal of interest captured by the image capturing apparatus and classifying, using a neural network, samples other than the signal of interest using a classifier having been determined using a first parameter based on information about the sample and a second parameter based on information identifying a position of the sample within the raw image data.

Abstract: An apparatus and method are provided to simultaneously provide good image quality and fast image reconstruction from magnetic resonance imaging (MRI) data by selecting an appropriate value for the regularization parameter used in compressed sensing (CS) image reconstruction. In CS reconstruction a high-resolution image can be reconstructed from randomized undersampled data by imposing sparsity in multi-scale transformation (e.g., wavelet) domain. Further, in the transformation domain, a threshold can be determined between signal and noise levels of the transform coefficients. A regularization parameter based on this threshold scales the regularization term, which imposes sparsity, relative to the data fidelity term in an objective function, thereby balancing the tradeoff between noise and smoothing.

Abstract: An MRI system includes processing circuitry configured to generate two or more RF pulses to form a spin echo, wherein each RF pulse corresponds to selecting at least two slice locations. Additionally, the MRI system encodes magnetic resonance (MR) magnetization to form echo signal data for each RF pulse, applies a set of time-shifts to a slice-selection gradient for each selected slice location, generates a pattern of slice-position-dependent moments on the echo signal data based on the set of time-shifts to the slice-selection gradient, receives image data corresponding to the echo signal data, and reconstructs the image data to form a plurality of images, wherein each of the plurality of images corresponds to one of the selected slice locations.

Abstract: An apparatus and method are disclosed for determining a time origin of an input RF pulse of a plurality of input RF pulses. The method includes generating an RF echo based on the plurality of input RF pulses, a time-duration between the input RF pulses being controllable in order to determine a time instance corresponding to an ideal position of the RF echo. The method further includes acquiring a data signal corresponding to a scan of a subject, and computing a time-difference between a measured peak of the acquired data signal and the time instance corresponding to the ideal position of the RF echo, the computed time difference corresponding to a measure of a time-shift of an effective magnetic center of the input RF pulse.

Abstract: An MRI system includes processing circuitry configured to generate two or more RF pulses to form a spin echo, wherein each RF pulse corresponds to selecting at least two slice locations. Additionally, the MRI system encodes magnetic resonance (MR) magnetization to form echo signal data for each RF pulse, applies a set of time-shifts to a slice-selection gradient for each selected slice location, generates a pattern of slice-position-dependent moments on the echo signal data based on the set of time-shifts to the slice-selection gradient, receives image data corresponding to the echo signal data, and reconstructs the image data to form a plurality of images, wherein each of the plurality of images corresponds to one of the selected slice locations.

Abstract: Described herein is an apparatus and method for determining a time origin of an input RF pulse of a plurality of input RF pulses. The method includes generating an RF echo based on the plurality of input RF pulses, a time-duration between the input RF pulses being controllable in order to determine a time instance corresponding to an ideal position of the RF echo. The method further includes acquiring a data signal corresponding to a scan of a subject, and computing a time-difference between a measured peak of the acquired data signal and the time instance corresponding to the ideal position of the RF echo, the computed time difference corresponding to a measure of a time-shift of an effective magnetic center of the input RF pulse.