Abstract: A method for generating an image of an object with a magnetic resonance imaging (MM) system is presented. The method includes first performing a calibration scan of the object. The calibration scan is performed with a zero echo time (ZTE) radial sampling scheme to obtain calibration k-spaces for surface coil elements and a body coil of the MRI system. The calibration scan is performed in such a manner that the endpoints of calibration k-space lines in each calibration k-space follow a spiral path. A plurality of calibration parameters are then obtained from the plurality of calibration k-spaces. A second scan of the object is then performed to acquire the MR image data. The image of the object is then generated based on the plurality of calibration parameters and the MR image data.

Abstract: Methods and systems are provided for segmenting structures in medical images. In one embodiment, a method includes receiving an input dataset including a set of medical images, a structure list specifying a set of structures to be segmented, and a segmentation protocol, performing an input check on the input dataset, determining whether each medical image of the set of medical images has passed the input check and removing any medical images from the set of medical images that do not pass the input check to form a final set of medical images, segmenting each structure from the structure list using one or more segmentation models and the final set of medical images, receiving a set of segmentations output from the one or more segmentation models, processing the set of segmentations to generate a final set of segmentations, and displaying and/or saving in memory the final set of segmentations.

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 magnetic resonance (MR) dynamically imaging method is provided. The method includes acquiring a functional MR dataset including frames of k-space datasets, while a functional stimulus is applied to the subject. Acquiring the functional MR dataset includes, acquiring a frame of k-space datasets by setting an orientation as an initial angle, and acquiring a free induction decay (FID) dataset. Acquiring an FID dataset includes applying a sequence of gradients, each gradient of the sequence corresponding to a k-space spoke, wherein the sequence of k-space spokes define a k-space segment having the orientation in a 3D k-space volume. Acquiring a frame of k-space datasets also includes acquiring a gradient echo dataset corresponding to the FID dataset, and updating the orientation as golden angles. The method also includes generating anatomical MR images and functional images based on the functional MR dataset.

Abstract: Various methods and systems are provided for translating magnetic resonance (MR) images to pseudo computed tomography (CT) images. In one embodiment, a method comprises acquiring an MR image, generating, with a multi-task neural network, a pseudo CT image corresponding to the MR image, and outputting the MR image and the pseudo CT image. In this way, the benefits of CT imaging with respect to accurate density information, especially in sparse regions of bone which exhibit with high dynamic range, may be obtained in an MR-only workflow, thereby achieving the benefits of enhanced soft-tissue contrast in MR images while eliminating CT dose exposure for a patient.

Abstract: A magnetic resonance (MR) dynamically imaging method is provided. The method includes acquiring a functional MR dataset including frames of k-space datasets, while a functional stimulus is applied to the subject. Acquiring the functional MR dataset includes, acquiring a frame of k-space datasets by setting an orientation as an initial angle, and acquiring a free induction decay (FID) dataset. Acquiring an FID dataset includes applying a sequence of gradients, each gradient of the sequence corresponding to a k-space spoke, wherein the sequence of k-space spokes define a k-space segment having the orientation in a 3D k-space volume. Acquiring a frame of k-space datasets also includes acquiring a gradient echo dataset corresponding to the FID dataset, and updating the orientation as golden angles. The method also includes generating anatomical MR images and functional images based on the functional MR dataset.

Abstract: A method for generating motion-corrected medical images includes obtaining, via a processor, k-space data of a region of interest acquired by a magnetic resonance imaging system utilizing a 3D radial pulse sequence with ZTE acquisition including optional magnetization preparation pulses. The method also includes sampling, via the processor, the k-space data to obtain a plurality of interleaved k-space segments. The method further includes reconstructing, via the processor, one or more interleaved k-space segments of the plurality of interleaved k-space segments to generate a respective motion navigator volume. The method even further includes co-registering, via the processor, each respective motion navigator volume to estimate motion and performing motion correction on the one or more interleaved k-space segments and their corresponding k-space trajectories.

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: Systems and methods for ZTE MRI are disclosed. An exemplary method includes obtaining Larmor frequencies of water and/or fat for a region of interest of a subject to be imaged at a pre-scan and setting a center frequency for an RF transceiver of the MR system at a value between the Larmor frequencies of water and fat. A ZTE pulse sequence is applied to the subject and MR signals in response to the ZTE pulse sequence are received from the subject. The received MR signals are demodulated with the center frequency and an in-phase ZTE image is generated from the demodulated MR signals.

Abstract: Systems and methods for ZTE MRI are disclosed. An exemplary method includes obtaining Larmor frequencies of water and/or fat for a region of interest of a subject to be imaged at a pre-scan and setting a center frequency for an RF transceiver of the MR system at a value between the Larmor frequencies of water and fat. A ZTE pulse sequence is applied to the subject and MR signals in response to the ZTE pulse sequence are received from the subject. The received MR signals are demodulated with the center frequency and an in-phase ZTE image is generated from the demodulated MR signals.

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: A system for magnetic resonance imaging an object with a plurality of readout gradient amplitudes is provided. The system includes a magnet assembly and a controller. The controller is operative to acquire MR data from the object via the magnet assembly. At least two portions of the MR data are acquired with different readout gradient amplitudes of the plurality.

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: 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: 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: 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: 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.

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: A system and method for estimating image intensity bias and segmentation tissues is presented. The system and method includes obtaining a first image data set and at least a second image data set, wherein the first and second image data sets are representative of an anatomical region in a subject of interest. Furthermore, the system and method includes generating a baseline bias map by processing the first image data set. The system and method also includes determining a baseline body mask by processing the second image data set. In addition, the system and method includes estimating a bias map corresponding to a sub-region in the anatomical region based on the baseline body mask. Moreover, the system and method includes segmenting one or more tissues in the anatomical region based on the bias map.