Abstract:
Methods and systems to obtain and apply T2 preparatory radiofrequency (RF) pulse sequences for magnetic resonance imaging (MRI) are provided. The iterative methods may employ propagation of the magnetization state of the object being imaged and a comparison with a target magnetization state. The methods disclosed may be used to obtain MRI pulse sequences that may optimize T2 relaxation contrast. The produced RF pulse sequences may be robust to effects from inhomogeneity of the magnetic fields or other environmental or physiological perturbations.
Abstract:
A system and method for tracking temperature changes in tissue and bone is disclosed. In one aspect, the temperature changes are tracked simultaneously with high spatial encoding and temporal efficiency. The method is robust in terms of B0 and chemical shift off-resonance, as well as insensitive to eddy currents for accurate temperature mapping. Zero TE (ZTE) based MR thermometry is utilized herein to extract temperature changes from proton density and T1 weighted images. Additionally, T1 signal contamination is corrected for by calibrating T1 and B0 by using a variable flip angle method to achieve temperature mapping in bone, aqueous and adipose tissue simultaneously.
Abstract:
Exemplary embodiments of the present disclosure are directed to scheduling positron emission tomography (PET) scans for a combined PET-MRI scanner based on an acquisition of MR scout images of a subject. An anatomy and orientation of the subject can be determined based on the MR scout images and the schedule for acquiring PET scans of the subject can be determined from the anatomy of the subject. The schedule generated using exemplary embodiments of the present disclosure can specify a sequence of bed positions, scan durations at each bed position, and whether respiratory gating will be used at one or more of the bed positions.
Abstract:
An imaging system and method are disclosed. An MR image and measured B0 field map of a target volume in a subject are reconstructed, where the MR image includes one or more bright and/or dark regions. One or more distinctive constituent materials corresponding to the bright regions are identified. Each dark region is iteratively labeled as one or more ambiguous constituent materials. Susceptibility values corresponding to each distinctive and iteratively labeled ambiguous constituent material is assigned. A simulated B0 field map is iteratively generated based on the assigned susceptibility values. A similarity metric is determined between the measured and simulated B0 field maps. Constituent materials are identified in the dark regions based on the similarity metric to ascertain corresponding susceptibility values. The MRI data is corrected based on the assigned and ascertained susceptibility values. A diagnostic assessment of the target volume is determined based on the corrected MRI data.
Abstract:
Methods and systems for production of silent, multi-gradient-echo, magnetic resonance images are provided. The methods employ iterative application of small updates to the magnetic field gradient followed by a short, non-selective radiofrequency pulse excitation and for free induction decay data acquisition. The magnetic field gradient updates allow for silent, self-refocusing pulse sequence. Subsequent applications of the magnetic field gradients allow for multiple echo data acquisitions, which may allow fast, silent production of T2*-weighted images.
Abstract:
Systems and methods of classifying component tissues of magnetic resonance images, where the method includes performing a proton density weighted, short echo-time magnetic resonance imaging measurement over a first volume field-of-view region of interest (ROI), repeating a series refining the first volume field-of-view ROI into a plurality of subsequent smaller ROI volumes having respective smaller resolutions, reconstructing a complex image from the plurality of magnetic resonance imaging measurements, performing a bias correction on at least one of the plurality of subsequent smaller ROI volumes, and classifying the ROI volumes by tissue type based on the bias-corrected image signal, wherein at least one tissue type is bone. A non-transitory medium containing processor instructions and a system are disclosed.
Abstract:
According to some embodiments, emission projection data and second source scan data are received. A prior map and a prior weight map are generated from second source scan data. A penalty function calculates voxel-wise differences between the prior map and a given image, transforms the voxel-wise differences and calculates a weighted sum of the transformed differences, using weights based on the prior weight map. Joint reconstruction of an emission image and an attenuation map proceeds iteratively and uses the penalty function.
Abstract:
Systems and methods for determining electrical properties using Magnetic Resonance Imaging (MRI) are provided. One method includes applying an ultra-short echo time (TE) pulse sequence in a Magnetic Resonance Imaging (MRI) system and acquiring a complex B1+B1− quantity from an object following the application of the ultra-short TE pulse sequence, where B1+ is a complex amplitude of a transmit radio-frequency (RF) magnetic field and B1− is a complex amplitude of a receive RF magnetic field. The method also includes estimating, with a processor, one or more electrical properties of the object using the complex amplitudes of the transmit RF magnetic field and the receive RF magnetic field.
Abstract:
An imaging system and method are disclosed. An MR image and measured B0 field map of a target volume in a subject are reconstructed, where the MR image includes one or more bright and/or dark regions. One or more distinctive constituent materials corresponding to the bright regions are identified. Each dark region is iteratively labeled as one or more ambiguous constituent materials. Susceptibility values corresponding to each distinctive and iteratively labeled ambiguous constituent material is assigned. A simulated B0 field map is iteratively generated based on the assigned susceptibility values. A similarity metric is determined between the measured and simulated B0 field maps. Constituent materials are identified in the dark regions based on the similarity metric to ascertain corresponding susceptibility values. The MRI data is corrected based on the assigned and ascertained susceptibility values. A diagnostic assessment of the target volume is determined based on the corrected MRI data.
Abstract:
The system and method of the invention pertains to automated analysis and reconstruction of images from a plurality of imaging devices to determine the presence of different types of artifacts, using signal processing and machine learning algorithms. The method (1) classifies the artifacts according to their cause, (2) selects correction algorithms to address the artifact, or artifact-generating data, and (3) selects the data or sections of the data and/or reconstruction parameters to be corrected. Then, another reconstruction is performed with the selected artifact corrections, yielding a second reconstructed image with less artifact content. The process can be applied iteratively until the artifact content of the reconstructed image is reduced to a satisfactory low level as determined by a user. If the artifacts cannot be addressed by data processing means, the method initiates or recommends alternative artifact management actions.