Abstract: Methods and apparatuses for quality control in image space for processing with an input data set are disclosed. A method includes providing an image object, including multiple voxels, and an input data set. A data model is determined from the image object. A cumulative distribution function (CDF) for the input data set is determined from the data model and the input data set based on a plurality of projections. The CDF is transformed to an image cumulative distribution function (ICDF) in object space. The ICDF represents a number of standard deviations associated with each voxel of the image object. The output of the ICDF is displayed. A nuclear imaging system and a computer readable storage medium are also disclosed. Techniques disclosed herein facilitate efficient quality control for tomographic image reconstruction.

Abstract: Computer-implemented methods of reconstructing an image object for a measured object in object space from image data in data space include causing a computer to execute instructions for providing zonal information separating the object space into at least two zones, providing at least two zonal image objects, each zonal image object being associated with one of the at least two zones, reconstructing the image object using a data model derived from forward projecting the zonal image objects into data space, wherein the contribution of each zonal image object to the data model is weighted according to a zonal scaling factor, and outputting the image object.

Abstract: An iterative reconstruction method to reconstruct an object includes determining, in a series of iteration steps, updated objects, wherein each iteration step includes determining a data model from an input object, and determining a stop-criterion of the data model on the basis of a chi-square-gamma statistic. The method further includes determining that the stop-criterion of the data model has transitioned from being outside the limitation of a preset threshold value to being inside the limitation, ending the iterations, and selecting one of the updated objects to be the reconstructed object.

Abstract: Computer-implemented methods of reconstructing an image object for a measured object in object space from image data in data space include causing a computer to execute instructions for providing zonal information separating the object space into at least two zones, providing at least two zonal image objects, each zonal image object being associated with one of the at least two zones, reconstructing the image object using a data model derived from forward projecting the zonal image objects into data space, wherein the contribution of each zonal image object to the data model is weighted according to a zonal scaling factor, and outputting the image object.

Abstract: An apparatus and method are provided for optimizing an amount of radiation dose and acquisition time in cardiac Single Photon Emission Computed Tomography (SPECT) imaging. The apparatus and method include providing an organ, acquiring images of the organ at projected views. Then a projected view that projects the organ as an annulus is selected; a region of interest (ROI) is also selected in the projected view, wherein the ROI is in a lateral wall of the organ. An average count in the ROI is determined; and an image quality of a reconstructed image based on the average count is predicted.

Abstract: A system for calming a patient positioned in a medical imaging device for imaging a patient. The system includes a scanner configured to generate scan data of a patient volume or area. The system also includes 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. In addition the system includes a patient bed for supporting the patient and status indicator lights for providing biofeedback to the patient that is indicative of breathing.

Abstract: A method of clinical collaboration between a clinical site and an analysis site includes receiving scan data from a scanner via a first reconstruction computer system at the clinical site, implementing a reconstruction procedure on the received scan data using a second reconstruction computer system at the analysis site and configured in accordance with a reconstruction configuration parameter, the analysis site being remote from the clinical site, and transmitting data indicative of the reconstruction configuration parameter to the first reconstruction computer system to configure the first reconstruction computer system in accordance with the reconstruction configuration parameter.

Abstract: The point spread function of a multi-channel collimator is modeled in photon imaging. The geometric aperture used in the point spread function is expanded to account for penetration, scattering, and/or imperfections of the collimator. The aperture is broadened using a weight that is a function of the distance of the source from the collimator. Rather than scaling the point spread function itself, the geometric aperture used in the point spread function is scaled to an effective aperture. The distance and geometric constraints may be used to determine the geometric aperture, but an additional broadening occurs as a function of the distance to account for non-ideal photon paths of travel. This additional broadening may improve the fidelity with respect to measured data relative to purely geometric or Gaussian models.

Abstract: Computer-implemented methods of reconstructing an image object for a measured object in object space from image data in data space include causing a computer to execute instructions for providing zonal information separating the object space into at least two zones, providing at least two zonal image objects, each zonal image object being associated with one of the at least two zones, reconstructing the image object using a data model derived from forward projecting the zonal image objects into data space, wherein the contribution of each zonal image object to the data model is weighted according to a zonal scaling factor, and outputting the image object.

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: Segmentation is provided in multi-modal reconstruction of functional information. Rather than using HU values for segmentation, the HU values are converted into linear attenuation coefficients, such as in a ?-map (Mu map). The conversion uses different functions for different ranges of the HU values. Linear attenuation coefficients are less likely subject to variation by patient, protocol, or scanner. The resulting segmentation may be more consistent across various clinical settings, providing for more accurate multi-modal reconstruction.

Abstract: A method for obtaining nuclear medical images of a patient in which one or more first images are obtained. The one or more first images can be used to identify one or more regions of interest for subsequent images that focus on the regions of interest. The process can occur iteratively until it is determined, either by a physician or a computer program that sufficient images have been obtained to identify lesions or other pathology within a reasonable level of confidence.

Abstract: An iterative reconstruction method to reconstruct an object includes determining, in a series of iteration steps, updated objects, wherein each iteration step includes determining a data model from an input object, and determining a stop-criterion of the data model on the basis of a chi-square-gamma statistic. The method further includes determining that the stop-criterion of the data model has transitioned from being outside the limitation of a preset threshold value to being inside the limitation, ending the iterations, and selecting one of the updated objects to be the reconstructed object.

Abstract: Emission tomography is registered with computed tomography or other modality in reconstruction. The anatomical information is used in the emission tomography reconstruction. In addition to an initial registration to use the anatomical information in the reconstruction, the registration is refined one or more times during other iterations refining the reconstruction of the emission volume. The registration is performed as part of the reconstruction. This multi-modal reconstruction may result in an emission tomography volume better aligned with the anatomical information.

Abstract: An imaging system includes interleaved emission detectors and transmission detectors. Emission detectors and transmission detectors can be interleaved along the axis of relative patient motion. Emission detectors and transmission detectors can be interleaved orthogonal to the axis of relative patient motion. Emission detectors can be single photon emission computed tomography detectors and the transmission detectors can be x-ray computed tomography detectors.

Abstract: A method for tomographic nuclear imaging determines the distance between a non-parallel hole collimator surface and a region of interest (ROI) by obtaining difference images between images acquired at different view angles of the ROI. The distance may be used in a nuclear image reconstruction algorithm to more accurately reconstruct an image of the ROI. The method takes advantage of the non-stationary Point Spread Function of a non-parallel hole collimator to determine depth information of gamma events emitted from the ROI.

Abstract: A computer-implemented method of presenting an image of an object includes causing a computer to execute instructions for providing a signal distribution of values N, generating a transformed distribution by calculating, for each value N, a transformed value X=?{square root over (N+?)}, and outputting the transformed distribution.

Abstract: Methods and apparatuses for quality control in image space for processing with an input data set are disclosed. A method includes providing an image object, including multiple voxels, and an input data set. A data model is determined from the image object. A cumulative distribution function (CDF) for the input data set is determined from the data model and the input data set based on a plurality of projections. The CDF is transformed to an image cumulative distribution function (ICDF) in object space. The ICDF represents a number of standard deviations associated with each voxel of the image object. The output of the ICDF is displayed. A nuclear imaging system and a computer readable storage medium are also disclosed. Techniques disclosed herein facilitate efficient quality control for tomographic image reconstruction.

Abstract: Tomographically reconstructing a 3D image object corresponding to a data set includes for each step in a series of iteration steps, determining an updated object by performing a combined operation, which includes performing an update operation for updating an input object and performing a pixon smoothing operation, and following a last iteration, outputting one of the updated objects as the 3D image object.

Abstract: An apparatus and method are provided for optimizing an amount of radiation dose and acquisition time in cardiac Single Photon Emission Computed Tomography (SPECT) imaging. The apparatus and method include providing an organ, acquiring images of the organ at projected views. Then a projected view that projects the organ as an annulus is selected; a region of interest (ROI) is also selected in the projected view, wherein the ROI is in a lateral wall of the organ. An average count in the ROI is determined; and an image quality of a reconstructed image based on the average count is predicted.