Abstract: A method of controlling and processing data from a hybrid PET-MR imaging system includes acquiring a positron emission tomographic (PET) dataset over a time period, wherein the PET dataset is affected by a quasi-periodic motion of the patient, and acquiring magnetic resonance (MR) data during the time period such that the acquisition time of the MR data relative to the PET dataset is known. A characteristic of the patient motion is then determined based on the PET dataset and the MR data is processed based on the characteristic of patient motion.

Abstract: A method of controlling and processing data from a hybrid PET-MR imaging system includes acquiring a positron emission tomographic (PET) dataset over a time period, wherein the PET dataset is affected by a quasi-periodic motion of the patient, and acquiring magnetic resonance (MR) data during the time period such that the acquisition time of the MR data relative to the PET dataset is known. A characteristic of the patient motion is then determined based on the PET dataset and the MR data is processed based on the characteristic of patient motion.

Abstract: A system and method for magnetic resonance imaging is disclosed, the MRI apparatus comprising a computer programmed to acquire a plurality of 3D MR data sets, each 3D MR data set acquired using a central transmit frequency and a central receive frequency set to an offset frequency value that is distinct for each 3D MR data set, wherein at least a portion of each 3D MR data set is accelerated k-space data, and wherein at least one of the plurality of 3D MR data sets comprises fully-sampled calibration k-space data lines. The computer is also programmed to determine reconstruction weights from the fully-sampled calibration k-space data lines, reconstruct an image for each 3D MR data set using the reconstruction weights from the fully-sampled calibration k-space data lines to synthesize unacquired data, and generate a composite image from the reconstructed images based on the plurality of 3D MR data sets.

Abstract: A method for generating a magnetic resonance (MR) image includes acquiring calibration data from each of a plurality of RF source coils. Calibration data for a virtual coil is generated based on the calibration data from the plurality of RF source coils and a set of synthesis weights is generated based on the calibration data from the plurality of RF source coils and the calibration data for the virtual coil. Accelerated MR data is acquired from each of the plurality of RF source coils. An image can be reconstructed based on an application of the set of synthesis weights to the accelerated MR data from the plurality of RF source coils.

Abstract: A system and method for magnetic resonance imaging is disclosed, the MRI apparatus comprising a computer programmed to acquire a plurality of 3D MR data sets, each 3D MR data set acquired using a central transmit frequency and a central receive frequency set to an offset frequency value that is distinct for each 3D MR data set, wherein at least a portion of each 3D MR data set is accelerated k-space data, and wherein at least one of the plurality of 3D MR data sets comprises fully-sampled calibration k-space data lines. The computer is also programmed to determine reconstruction weights from the fully-sampled calibration k-space data lines, reconstruct an image for each 3D MR data set using the reconstruction weights from the fully-sampled calibration k-space data lines to synthesize unacquired data, and generate a composite image from the reconstructed images based on the plurality of 3D MR data sets.

Abstract: A method for generating a magnetic resonance (MR) image includes acquiring calibration data from each of a plurality of RF source coils. Calibration data for a virtual coil is generated based on the calibration data from the plurality of RF source coils and a set of synthesis weights is generated based on the calibration data from the plurality of RF source coils and the calibration data for the virtual coil. Accelerated MR data is acquired from each of the plurality of RF source coils. An image can be reconstructed based on an application of the set of synthesis weights to the accelerated MR data from the plurality of RF source coils.

Abstract: A system and method for parallel imaging is disclosed that generates linear combination coefficient weights by solving systems of linear equations formulated with correlation values. An MRI apparatus includes a computer programmed to acquire MR data from an imaging volume for a plurality of encoding locations using an array of RF receiver coils. Correlation values are calculated from the MR data. From these calculated correlation values, synthesis weights are generated. An image is then reconstructed based on an application of the synthesis weights to at least a portion of the MR data acquired from the array of RF receiver coils.

Abstract: The present invention provides a system and method for parallel imaging that performs auto-calibrating reconstructions with a 2D (for 2D imaging) or 3D kernel (for 3D imaging) that exploits the computational efficiencies available when operating in certain data “domains” or “spaces”. The reconstruction process of multi-coil data is separated into a “training phase” and an “application phase” in which reconstruction weights are applied to acquired data to synthesize (replace) missing data. The choice of data space, i.e., k-space, hybrid space, or image space, in which each step occurs is independently optimized to reduce total reconstruction time for a given imaging application. As such, the invention retains the image quality benefits of using a 2D k-space kernel without the computational burden of applying a 2D k-space convolution kernel.

Abstract: A system and method for determining motion in a region-of-interest directly from MR data acquired from the region-of-interest and independently of k-space trajectory are disclosed.

Abstract: A system and method for MR imaging includes the use of a form of autocalibrated parallel imaging. By combining a segmented, rotated acquisition trajectory with autocalibration parallel imaging (API), the system and method can achieve improved motion insensitivity while maintaining the benefits of accelerated acquisition due to parallel imaging. In various embodiments, calibration values from a set of reference data or from another set of imaging data can be used in determining reconstruction weights for a given k-space data set. Thus, separate calibration data need not necessarily be acquired for each set of imaging data.

Abstract: The present invention provides a system and method for parallel imaging that performs auto-calibrating reconstructions with a 2D (for 2D imaging) or 3D kernel (for 3D imaging) that exploits the computational efficiencies available when operating in certain data “domains” or “spaces”. The reconstruction process of multi-coil data is separated into a “training phase” and an “application phase” in which reconstruction weights are applied to acquired data to synthesize (replace) missing data. The choice of data space, i.e., k-space, hybrid space, or image space, in which each step occurs is independently optimized to reduce total reconstruction time for a given imaging application. As such, the invention retains the image quality benefits of using a 2D k-space kernel without the computational burden of applying a 2D k-space convolution kernel.

Abstract: An RF coil assembly includes a plurality of RF source coils and an RF target coil separate from the plurality of RF source coils. A computer is programmed to acquire MR data of an imaging object from each of the plurality of RF source coils and to acquire MR data of the imaging object from the RF target coil. The computer is further programmed to calculate a set of weights based on a relationship between MR data acquired from each RF source coil and MR data acquired from the RF target coil and to reconstruct an image based on an application of the set of weights to at least a portion of the MR data acquired from each of the plurality of RF source coils.

Abstract: The present invention provides a system and method for parallel imaging that performs auto-calibrating reconstructions with a 2D (for 2D imaging) or 3D kernel (for 3D imaging) that exploits the computational efficiencies available when operating in certain data “domains” or “spaces”. The reconstruction process of multi-coil data is separated into a “training phase” and an “application phase” in which reconstruction weights are applied to acquired data to synthesize (replace) missing data. The choice of data space, i.e., k-space, hybrid space, or image space, in which each step occurs is independently optimized to reduce total reconstruction time for a given imaging application. As such, the invention retains the image quality benefits of using a 2D k-space kernel without the computational burden of applying a 2D k-space convolution kernel.

Abstract: A system and method for MR imaging includes the use of a form of autocalibrated parallel imaging. By combining a segmented, rotated acquisition trajectory with autocalibration parallel imaging (API), the system and method can achieve improved motion insensitivity while maintaining the benefits of accelerated acquisition due to parallel imaging. In various embodiments, calibration values from a set of reference data or from another set of imaging data can be used in determining reconstruction weights for a given k-space data set. Thus, separate calibration data need not necessarily be acquired for each set of imaging data.

Abstract: An RF coil assembly includes a plurality of RF source coils and an RF target coil separate from the plurality of RF source coils. A computer is programmed to acquire MR data of an imaging object from each of the plurality of RF source coils and to acquire MR data of the imaging object from the RF target coil. The computer is further programmed to calculate a set of weights based on a relationship between MR data acquired from each RF source coil and MR data acquired from the RF target coil and to reconstruct an image based on an application of the set of weights to at least a portion of the MR data acquired from each of the plurality of RF source coils.

Abstract: The present invention provides a system and method for parallel imaging that performs auto-calibrating reconstructions with a 2D (for 2D imaging) or 3D kernel (for 3D imaging) that exploits the computational efficiencies available when operating in certain data “domains” or “spaces”. The reconstruction process of multi-coil data is separated into a “training phase” and an “application phase” in which reconstruction weights are applied to acquired data to synthesize (replace) missing data. The choice of data space, i.e., k-space, hybrid space, or image space, in which each step occurs is independently optimized to reduce total reconstruction time for a given imaging application. As such, the invention retains the image quality benefits of using a 2D k-space kernel without the computational burden of applying a 2D k-space convolution kernel.

Abstract: Noninvasive, MR-compatible methods and systems optically detect mechanical cardiac activity by anatomic (e.g., esophageal) movements. Most preferably, esophageal motion is detected optically and is indicative rhythmic cardiac activities. This esophageal motion may then be detected and used to provide a signal indicative of periods of cardiac activity and inactivity. The signal may be further processed so as to generate a trigger signal that may be input to a MR scanner. In such a manner, MR microscopy may be accomplished to acquire information at a specific phase of the cardiac cycle, for example, in synchrony with periods of cardiac inactivity. Moreover, since mechanical cardiac activity is detected and employed, instead of electrical activity as is employed in conventional techniques, the present invention is immune to electromagnetic interference during MR microscopy. As a result, robust cardiac signals may be monitored and gated during 2-dimensional and 3-dimensional in vivo microscopy.