Abstract: In this disclosure, a process of imaging a target object using magnetic resonance (MR) includes an MRI scanner scanning the target object using a first transmit RF pulse. A processor associated with the MRI scanner can acquire magnitude and/or phase data associated with a first RF signal produced (or echoed) by the target object responsive to the MRI scan. The processor can determine a second transmit RF pulse for use to scan the target object based on the acquired data and according to a given phase criterion. The phase criterion can be configured to enforce mitigation of a phase distribution estimated based on the acquired data.

Abstract: A method of nuclear magnetic resonance imaging of an object is disclosed, the method including: receiving MR data including magnitude and phase information generated using an MR scan having a series of different echo times; generating one or more measured MR images based on the MR data; and processing the measured MR images to generate unaliased or substantially unaliased phase information for at least one pixel in the image.

Abstract: A method is disclosed including: receiving a time resolved series of magnetic resonance (MR) images of an imaged region of a subject; processing the images to generate comparison data by comparing a temporal behavior of a reference region of the MR images to at least one other region of the MR images; an generating an output based on the comparison data. The method may be applied in a variety of contexts, including perfusion weighted imaging, determination of T2*, and other time series functions.

Abstract: A method of generating a susceptibility map of an object utilizes a regularizing inverse function, oversampling k-space, removing external phase noise and rapid phase change effects, accounting for the known geometry of the object, and using modified SWI phase data to generate reasonable susceptibility maps and digital images therefrom, such as SWI images. The inventors refers to the inventive methods set forth herein as Susceptibility Weighted Imaging and Mapping (SWIM).

Abstract: A method of generating a susceptibility map of an object utilizes a regularizing inverse function, oversampling k-space, removing external phase noise and rapid phase change effects, accounting for the known geometry of the object, and using modified SWI phase data to generate reasonable susceptibility maps and digital images therefrom, such as SWI images. The inventors refers to the inventive methods set forth herein as Susceptibility Weighted Imaging and Mapping (SWIM).

Abstract: A method of generating a susceptibility map of an object utilizes a regularizing inverse function, oversampling k-space, removing external phase noise and rapid phase change effects, accounting for the known geometry of the object, and using modified SWI phase data to generate reasonable susceptibility maps and digital images therefrom, such as SWI images. The inventors refers to the inventive methods set forth herein as Susceptibility Weighted Imaging and Mapping (SWIM).

Abstract: A method of generating a susceptibility map of an object utilizes a regularizing inverse function, oversampling k-space, removing external phase noise and rapid phase change effects, accounting for the known geometry of the object, and using modified SWI phase data to generate reasonable susceptibility maps and digital images therefrom, such as SWI images. The inventors refers to the inventive methods set forth herein as Susceptibility Weighted Imaging and Mapping (SWIM).

Abstract: A method comprises digitally representing a volume of space as a plurality of voxels and assigning real and imaginary values derived from magnetic resonance imaging data of the space to each of the voxels. Furthermore, the method comprises a steps of calculating a first complex summation of the real and imaginary values of a first set of the voxels, and calculating a second complex summation of the real and imaginary values of a second set of the voxels. Each set of voxels represents a different region of the volume of space. The regions are concentric. The method also comprises steps of using the first and second summations, along with another value quantitatively calculated from the magnetic resonance imaging data, to calculate a value that is dependent upon the approximate magnetic moment of an object within the volume of space, and digitally representing and storing said value.

Abstract: A method comprises digitally representing a volume of space as a plurality of voxels and assigning real and imaginary values derived from magnetic resonance imaging data of the space to each of the voxels. Furthermore, the method comprises a steps of calculating a first complex summation of the real and imaginary values of a first set of the voxels, and calculating a second complex summation of the real and imaginary values of a second set of the voxels. Each set of voxels represents a different region of the volume of space. The regions are concentric. The method also comprises steps of using the first and second summations, along with another value quantitatively calculated from the magnetic resonance imaging data, to calculate a value that is dependent upon the approximate magnetic moment of an object within the volume of space, and digitally representing and storing said value.

Abstract: A method of removing noise while preserving signal in nuclear magnetic resonance images combines steps of performing a magnitude threshold filter and performing a phase threshold filter on the image data. Preferably, a magnitude and phase connectivity algorithm is applied to pixels that fail to meet either the magnitude or phase thresholds.

Abstract: A method of removing noise while preserving signal in nuclear magnetic resonance images combines steps of performing a magnitude threshold filter and performing a phase threshold filter on the image data. Preferably, a magnitude and phase connectivity algorithm is applied to pixels that fail to meet either the magnitude or phase thresholds.

Abstract: A method of complex image reconstruction from partially acquired data in two or more dimensions is presented. This method uses an iterative multidimensional transformation to reconstruct a magnetic resonance image. The method of this invention abandons the theory that complex conjugation is necessary to reconstruct a complex image from partially acquired data and, instead, utilizes a phase constraint to make the solution determinable using a multidimensional transformation technique. This method of image reconstruction allows magnetic resonance images to be reconstructed by acquiring only one-half of the k-space data.

Abstract: The echo time in an MR pulse sequence is optimized in accordance with the application desired. Advantageously, the echo time is selected to cause a partial volume signal cancellation from veins as compared with background tissue, and the MR pulse sequence is of a velocity-compensated type. MR data are acquired from gradient echoes. Multiple echoes may be used to extract information (such as volume content and susceptibility) about the material under investigation.