Abstract: A system and method include acquisition of a plurality of sets of images which meet acceptance criteria of an imaging task, each set of images acquired using a respective instance of a type of imaging component, acquisition of a test image using a test instance of the type of imaging component, presentation of a plurality of groups of images, each of the groups of images including the test image and a respective one or more images of the plurality of sets of images, reception, for each group of images, of an indication from an observer of a ranking of the test image of the group with respect to the respective one or more images of the group, and determination of a quality of the test instance of the type of imaging component based on the indications.

Abstract: A detector used for tomography imaging is mobile, allowing the detector to move about an object (e.g., patient to be imaged). A swarm of such detectors, such as a swarm of drones with detectors, may be used for tomography imaging. The trajectory or trajectories of the mobile detectors may account for the pose and/or movement of the object being imaged. The trajectory or trajectories may be based, in part, on the sampling for desired tomography. An image of an internal region of the object is reconstructed from detected signals of the mobile detectors using tomography.

Abstract: An emission image is generated from poor quality emission data. A machine-learned model may be used to recover information. Emission imaging may be provided due to the recovery in a way that at least some diagnostically useful information is made available despite corruption that would otherwise result in less diagnostically useful information or no image at all.

Abstract: A system and method include acquisition of a plurality of sets of images which meet acceptance criteria of an imaging task, each set of images acquired using a respective instance of a type of imaging component, acquisition of a test image using a test instance of the type of imaging component, presentation of a plurality of groups of images, each of the groups of images including the test image and a respective one or more images of the plurality of sets of images, reception, for each group of images, of an indication from an observer of a ranking of the test image of the group with respect to the respective one or more images of the group, and determination of a quality of the test instance of the type of imaging component based on the indications.

Abstract: A Compton camera for medical imaging is divided into segments with each segment including part of the scatter detector, part of the catcher detector, and part of the electronics. The different segments may be positioned together to form the Compton camera arcing around part of the patient space. By using segments, any number of segments may be used to fit with a multi-modality imaging system.

Abstract: A multi-modality imaging system allows for selectable photoelectric effect and/or Compton effect detection. The camera or detector is a module with a catcher detector. Depending on the use or design, a scatter detector and/or a coded physical aperture are positioned in front of the catcher detector relative to the patient space. For low energies, emissions passing through the scatter detector continue through the coded aperture to be detected by the catcher detector using the photoelectric effect. Alternatively, the scatter detector is not provided. For higher energies, some emissions scatter at the scatter detector, and resulting emissions from the scattering pass by or through the coded aperture to be detected at the catcher detector for detection using the Compton effect. Alternatively, the coded aperture is not provided. The same module may be used to detect using both the photoelectric and Compton effects where both the scatter detector and coded aperture are provided with the catcher detector.

Abstract: A detector used for tomography imaging is mobile, allowing the detector to move about an object (e.g., patient to be imaged). A swarm of such detectors, such as a swarm of drones with detectors, may be used for tomography imaging. The trajectory or trajectories of the mobile detectors may account for the pose and/or movement of the object being imaged. The trajectory or trajectories may be based, in part, on the sampling for desired tomography. An image of an internal region of the object is reconstructed from detected signals of the mobile detectors using tomography.

Abstract: A system and method include acquisition of a set of tomographic images of a patient volume associated with each of a plurality of timepoints of a first radiopharmaceutical therapy cycle, determination, for each of the plurality of timepoints, of a systematic uncertainty for each of a plurality of regions within the patient volume based on the set of tomographic images associated with the timepoint, determination, for each of the plurality of timepoints, of a quantitative statistical uncertainty based on the set of tomographic images associated with the timepoint, determination of a dose and a dose uncertainty for each of the plurality of regions based on the set of tomographic images, the systematic uncertainty and the quantitative statistical uncertainty for each of the plurality of timepoints, and display of a cumulative dose and cumulative dose uncertainty for each of the plurality of regions based on the dose and the dose uncertainty determined for each of the plurality of regions.

Abstract: A framework for quality-driven image processing. In accordance with one aspect, image data and anatomical data of a region of interest are received. Zonal information is generated based on the anatomical data. Image processing is performed based on the image data to generate an intermediate image. One or more image quality metrics may then be determined for the intermediate image data using the zonal information. A processing action may be performed based on the one or more image quality metrics to generate a final image.

Abstract: For calibration of internal dose in nuclear imaging, the dose model used for estimating internal dose in a patient is calibrated. One or more values of the dose model (e.g., a physics simulation, dose kernels, or a transport model) are set based on measured dose. The dose may be measured relative to specific tissues and/or isotopes, providing for tracer and tissue specific calibration. For example, dose from the tracer to be injected into the patient is estimated from emissions as well as measured by a dosimeter in a tissue mimicking tissue mimicking object. These doses are used to calibrate the dose model, which calibrated dose model is then used to determine internal dose for the patient.

Abstract: A system and method includes input of a plurality of sets of training data to a neural network to generate a plurality of sets of output data, determination of a first loss based on the plurality of sets of output data and on the plurality of sets of ground truth data, determination if a second loss based on the plurality of sets of output data and one or more physics-based constraints, and modification of the neural network based on the first loss and the second loss.

Abstract: Parameterized model reconstruction is used for internal dose tomography. The parameterized model, solved for within the reconstruction, models the dose level and may account for diffusion, isotope half-life, and/or biological half-life. Using the detected emissions from different scans (e.g., from different scan sessions in a given cycle) as input for the one reconstruction, the parameterized model reconstruction determines the biodistribution of dose at any time.

Abstract: A framework for characterization of a collimator. In accordance with one aspect, first and second sides of the collimator are photographed to generate first and second image data. An optical characterization map (OCM) may be generated based on the first and second image data, wherein the optical characterization map characterizes the individual channels of the collimator. Quality assessment or image reconstruction may then be performed based on the OCM.

Abstract: A system and method include training of an artificial neural network to generate an output data set, the training based on the plurality of sets of emission data acquired using a first imaging modality and respective ones of data sets acquired using a second imaging modality.

Abstract: For denoising in SPECT, such as qSPECT, machine learning is used to relate settings to noise structure. Given the SPECT imaging arrangement for a patient, the machine-learned model estimates the structure of the noise. This noise structure may be used to denoise the reconstructed representation.

Abstract: An emission image is generated from poor quality emission data. A machine-learned model may be used to recover information. Emission imaging may be provided due to the recovery in a way that at least some diagnostically useful information is made available despite corruption that would otherwise result in less diagnostically useful information or no image at all.

Abstract: A system includes a scanner configured to generate scan data of a patient volume or area, a processor configured to implement control operations, the control operations being directed to acquisition of the scan data or to processing of the scan data, and a monitoring system including a range imaging camera positioned for a field of view such that the monitoring system is configured to capture spatial data indicative of movement of an object spaced from the scanner. The processor is configured to implement an adjustment in the control operations based on the spatial data.

Abstract: In nuclear medical imaging, respiratory motion is corrected. Rather than pairwise estimation of motion from projection views, a sequence-based technique is used to jointly estimate parameters for a motion model across many projection views. In one approach, this sequence-based method is iteratively solved with a maximum likelihood objective function incorporating the motion model. A surrogate respiration signal is used to gate for the joint estimation and used to convert gated motion parameters to temporal motion parameters.

Abstract: For a multi-modal emission tomography system, an improved control system increases the likelihood of optimal image quality, satisfaction of physician goals, and/or avoids repetition in scanning and the corresponding increase in dose burden. The control system is divided into two or more arrangements. One arrangement receives goal information and outputs reconstruction settings and generic scan settings to satisfy the goal information. Another arrangement converts the generic scan settings to emission tomography system-specific scan settings, which are used to detect emissions. The separation of the arrangements allows independent operation so that different system-specific conversions may be used for different systems.

Abstract: Single photon emission computed tomography (SPECT) is performed with multiple emission energies. For quantitative or qualitative SPECT, the image formation process for emissions at different energy ranges is modeled (44, 46, 48, 50) separately. Different scatter, different attenuation, and/or different collimator-detector response models corresponding to different energy ranges are used in the reconstruction.