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:
Imaging system and method are presented. Emission scan (ES) and anatomical scan (AS) data corresponding to a target volume in a subject are received. One or more at least partial AS images are reconstructed using AS data. An image-space certainty (IC) map representing a confidence level (CL) for attenuation coefficients of selected voxels in AS images and a preliminary attenuation (PA) map based on AS images are generated. One or more of selected attenuation factors (AF) in projection-space are initialized based on PA map. A projection-space certainty (PC) map representing CL for the selected AF is generated based on IC map. An emission image of the target volume is initialized. The selected AF and emission image are iteratively updated based on the ES data, PC map, initial AF, and/or initial emission image. A desired emission image and/or AF values are determined based on the iteratively updated AF and/or emission image.
Abstract:
A system and method for detecting motion is presented. The system and method includes identifying a region of interest in the plurality of images corresponding to a subject of interest. Furthermore, the system and method includes determining signal characteristics corresponding to the region of interest. In addition, the system and method includes generating a composite signal, where the composite signal comprises an aggregate of the signal characteristics corresponding to the region of interest. The system and method also includes analyzing the composite signal to detect motion in the region of interest.
Abstract:
The disclosed approach employs a generic methodology for transforming individual modality specific multi-parametric data into data, e.g., maps or images, which provides direct insight into the underlying physiology of the tissue. This may facilitate better clinical evaluation of the disease data as well as help non-imaging technologists and scientist to directly correlate imaging findings with basic biological phenomenon being studied with imaging.
Abstract:
Imaging system and method are presented. Emission scan (ES) and anatomical scan (AS) data corresponding to a target volume in a subject are received. One or more at least partial AS images are reconstructed using AS data. An image-space certainty (IC) map representing a confidence level (CL) for attenuation coefficients of selected voxels in AS images and a preliminary attenuation (PA) map based on AS images are generated. One or more of selected attenuation factors (AF) in projection-space are initialized based on PA map. A projection-space certainty (PC) map representing CL for the selected AF is generated based on IC map. An emission image of the target volume is initialized. The selected AF and emission image are iteratively updated based on the ES data, PC map, initial AF, and/or initial emission image. A desired emission image and/or AF values are determined based on the iteratively updated AF and/or emission image.
Abstract:
A system and method for detecting motion is presented. The system and method includes identifying a region of interest in the plurality of images corresponding to a subject of interest. Furthermore, the system and method includes determining signal characteristics corresponding to the region of interest. In addition, the system and method includes generating a composite signal, where the composite signal comprises an aggregate of the signal characteristics corresponding to the region of interest. The system and method also includes analyzing the composite signal to detect motion in the region of interest.
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:
The present disclosure relates to a method for assessing biological features, the method that includes rendering a graphical user interface allowing a user to select patient cohort information defining one or more characteristics of a patient cohort and allowing a user to select an analysis technique from a plurality of analysis techniques, wherein the analysis technique operates on the patient data from both the first data acquisition modality and the second data acquisition modality to generate a derived variable. The method also includes allowing a user to define a threshold for the derived variable to define a first patient group above the threshold and a second patient group below the threshold for each patient of a patient cohort.
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:
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.