Abstract: Systems and methods include control of a nuclear imaging scanner to acquire nuclear imaging scan data of a body, control of a computed tomography scanner to acquire computed tomography scan data of the body, determination of a scanning speed, of the nuclear imaging scanner, associated with each of a plurality of scanning coordinates based on locations of one or more internal volumes associated with radioactivity greater than a threshold level, a classification determined for each of the one or more of the internal volumes indicating a degree of clinical interest based at least in part on the radioactivity associated with the internal volume, and an attenuation coefficient map based on the computed tomography scan data, and control of the nuclear imaging scanner to scan the body over each of the scanning coordinates at the associated scanning speed.

Abstract: Systems and methods for detecting and classifying clinical features in medical images are disclosed. Natural language processes are applied to speech received from a dictation system to determine clinical and anatomical information for a medical image being viewed. In some examples, gaze location information identifying an eye position is received, as well as an image position for the medical image being viewed. Features of the medical image are detected and classified based on machine learning models. Anatomical associations are generated based on one or more of the classifications, the anatomical information, the gaze information, and the image position. The machine learning models can be trained based on the anatomical associations. In some examples, reports are generated based on the anatomical associations.

Abstract: Systems and methods include control of a nuclear imaging scanner to acquire nuclear imaging scan data of a body, control of a computed tomography scanner to acquire computed tomography scan data of the body, identification of one or more internal volumes of the body based on the nuclear imaging scan data, each of the one or more internal volumes associated with radioactivity greater than a threshold level, determination, for each of the one or more internal volumes, of a classification indicating a degree of clinical interest based at least in part on the radioactivity associated with the internal volume, generation of an attenuation coefficient map based on the computed tomography scan data, determination of a scanning speed associated with each of a plurality of scanning coordinates based on locations of the one or more internal volumes, the classification determined for each of the one or more of the internal volumes, and the attenuation coefficient map, and control of the nuclear imaging scanner to scan t

Abstract: A method and system for determining system-based tumor burden is disclosed. In one aspect, the method includes obtaining the medical image from a source, through an interface. Additionally, the method includes identifying a first region of interest in the medical image. The method also includes selecting from the first region of interest a second region of interest whose tumor burden is to be determined. Furthermore, the method includes defining a segmentation criterion for the second region of interest. The method also includes determining the tumor burden for the second region of interest.

Abstract: Systems and methods for detecting and classifying clinical features in medical images are disclosed. Natural language processes are applied to speech received from a dictation system to determine clinical and anatomical information for a medical image being viewed. In some examples, gaze location information identifying an eye position is received, as well as an image position for the medical image being viewed. Features of the medical image are detected and classified based on machine learning models. Anatomical associations are generated based on one or more of the classifications, the anatomical information, the gaze information, and the image position. The machine learning models can be trained based on the anatomical associations. In some examples, reports are generated based on the anatomical associations.

Abstract: A system and method include execution of a first nuclear imaging scan to acquire first nuclear imaging scan data of a body; generation of a target image based on the first nuclear imaging scan data execute a second nuclear imaging scan to acquire second nuclear imaging scan data of the body association of each of a plurality of portions of the second nuclear imaging scan data with a respective one of a plurality of motion phases of the body, generation, for each of the plurality of motion phases of the body, of a binned image based on the portion of the second nuclear imaging scan data associated with the motion phase, performance of motion-correction on each of the plurality of binned images based on the target image to generate a plurality of motion-corrected binned images, and generation of an image based on the target image and the plurality of motion-corrected binned images.

Abstract: A method for performing magnetic resonance imaging with variable flip angle (VFA) readouts includes preparing longitudinal magnetization of a spin system associated with a subject to a target state, yielding a prepared longitudinal magnetization. The prepared longitudinal magnetization is converted to an image using a VFA readout sequence, wherein the VFA readout sequence comprises a plurality of radio-frequency pulses with corresponding flip-angles varying according to a modulation function.

Abstract: A system and method include execution of a first nuclear imaging scan to acquire first nuclear imaging scan data of a body; generation of a target image based on the first nuclear imaging scan data execute a second nuclear imaging scan to acquire second nuclear imaging scan data of the body association of each of a plurality of portions of the second nuclear imaging scan data with a respective one of a plurality of motion phases of the body, generation, for each of the plurality of motion phases of the body, of a binned image based on the portion of the second nuclear imaging scan data associated with the motion phase, performance of motion-correction on each of the plurality of binned images based on the target image to generate a plurality of motion-corrected binned images, and generation of an image based on the target image and the plurality of motion-corrected binned images.

Abstract: A method and system for determining system-based tumor burden is disclosed. In one aspect, the method includes obtaining the medical image from a source, through an interface. Additionally, the method includes identifying a first region of interest in the medical image. The method also includes selecting from the first region of interest a second region of interest whose tumor burden is to be determined. Furthermore, the method includes defining a segmentation criterion for the second region of interest. The method also includes determining the tumor burden for the second region of interest.

Abstract: A system and method includes identification of locations of one or more internal volumes of a body, each of the identified one or more locations associated with radioactivity greater than a threshold level, determination of a degree of interest associated with each of the one or more internal volumes based at least in part on the associated radioactivity, determination of a scanning speed associated with each of a plurality of scanning coordinates, based at least in part on the locations of the one or more internal volumes and the degree of interest associated with each of the one or more of the internal volumes, and control of the nuclear imaging scanner to scan the body based on the plurality of scanning speeds and associated scanning coordinates.

Abstract: A method for performing free breathing pixel-wise myocardial T1 parameter mapping includes performing a free-breathing scan of a cardiac region at a plurality of varying saturation recovery times to acquire a k-space dataset; generating an image dataset based on the k-space dataset; and performing a respiratory motion correction process on the image dataset. The respiratory motion correction process comprises selecting a target image from the image dataset, co-registering each image in the image dataset to the target image to determine a spatial alignment measurement for each image, and identifying a subset of the image dataset comprising images with the spatial alignment measurement above a predetermined value. Following the respiratory motion correction process, a pixel-wise fitting is performed on the image dataset to estimate T1 relaxation time values for the cardiac region. Then, a pixel-map of the cardiac region is produced depicting the T1 relaxation time values.

Abstract: A computer-implemented method for performing spatiotemporal background phase correction for phase contrast velocity encoded magnetic resonance imaging includes performing a phase contrast magnetic resonance imaging scan of a region of interest within a patient to yield a complex image and calculating a plurality of filter cut-off frequencies based on physiological limits associated with the patient. A spatiotemporal filter is created based on the plurality of filter cut-off frequencies. This spatiotemporal filter is applied to the complex image to yield a low-pass filtered complex image. Then, complex division is performed using the complex image and the low-pass filtered complex image to yield a corrected image.

Abstract: A computer-implemented method for performing spatiotemporal background phase correction for phase contrast velocity encoded magnetic resonance imaging includes performing a phase contrast magnetic resonance imaging scan of a region of interest within a patient to yield a complex image and calculating a plurality of filter cut-off frequencies based on physiological limits associated with the patient. A spatiotemporal filter is created based on the plurality of filter cut-off frequencies. This spatiotemporal filter is applied to the complex image to yield a low-pass filtered complex image. Then, complex division is performed using the complex image and the low-pass filtered complex image to yield a corrected image.

Abstract: A method for performing free breathing pixel-wise myocardial T1 parameter mapping includes performing a free-breathing scan of a cardiac region at a plurality of varying saturation recovery times to acquire a k-space dataset; generating an image dataset based on the k-space dataset; and performing a respiratory motion correction process on the image dataset. The respiratory motion correction process comprises selecting a target image from the image dataset, co-registering each image in the image dataset to the target image to determine a spatial alignment measurement for each image, and identifying a subset of the image dataset comprising images with the spatial alignment measurement above a predetermined value. Following the respiratory motion correction process, a pixel-wise fitting is performed on the image dataset to estimate T1 relaxation time values for the cardiac region. Then, a pixel-map of the cardiac region is produced depicting the T1 relaxation time values.

Abstract: A computer-implemented method for determining magnetic field inversion time of a tissue species includes generating a T1-mapping image of a tissue of interest, the T1-mapping image comprising a plurality of T1 values within an expected range of T1 values for the tissue of interest. An image mask is created based on predetermined identification information about the tissue of interest. Next, an updated image mask is created based on a largest connected region in the image mask. The updated image mask is applied to the T1-mapping image to yield a masked image. Then, a mean relaxation time value is determined for the largest connected region. The mean relaxation time value is then used to determine a time point for nulling longitudinal magnetization.

Abstract: A method for operating a Magnetic Resonance (MR) imaging system includes generating radio frequency (RF) excitation pulses in patient anatomy to provide subsequent acquisition of associated RF echo data and generating slice select magnetic field gradients for phase encoding and readout RF data acquisition in the patient anatomy. The method also includes acquiring a plurality of slices of an image within a plurality of cycles, each of the plurality of slices being acquired within each of the plurality of cycles and causing, by a control processor, a RF signal generator and a gradient generator to change an order that each of the plurality of slices is acquired between consecutive cycles of the plurality of cycles.

Abstract: Disclosed herein is a framework for facilitating waveform parameter estimation. In accordance with one aspect, time-based waveforms are generated based on analysis planes positioned along a centerline of the vessel. A surface may be fitted to upslope regions of the waveforms to determine one or more waveform parameters based on intersection of the surface with the upslope regions.

Abstract: Disclosed herein is a framework for facilitating waveform parameter estimation. In accordance with one aspect, time-based waveforms are generated based on analysis planes positioned along a centerline of the vessel. A surface may be fitted to upslope regions of the waveforms to determine one or more waveform parameters based on intersection of the surface with the upslope regions.

Abstract: A method for performing magnetic resonance imaging with variable flip angle (VFA) readouts includes preparing longitudinal magnetization of a spin system associated with a subject to a target state, yielding a prepared longitudinal magnetization. The prepared longitudinal magnetization is converted to an image using a VFA readout sequence, wherein the VFA readout sequence comprises a plurality of radio-frequency pulses with corresponding flip-angles varying according to a modulation function.

Abstract: A computer-implemented method for determining magnetic field inversion time of a tissue species includes generating a T1-mapping image of a tissue of interest, the T1-mapping image comprising a plurality of T1 values within an expected range of T1 values for the tissue of interest. An image mask is created based on predetermined identification information about the tissue of interest. Next, an updated image mask is created based on a largest connected region in the image mask. The updated image mask is applied to the T1-mapping image to yield a masked image. Then, a mean relaxation time value is determined for the largest connected region. The mean relaxation time value is then used to determine a time point for nulling longitudinal magnetization.