Abstract: A spectral computed tomography imaging system (102) includes a radiation source (112) configured to emit x-ray radiation and a detector array (114) configured to detect x-ray radiation and generate spectral data. The spectral imaging system further includes a memory (134) configured to store a virtual non-contrast image enhancing module (136) that includes computer executable instructions including a neural network trained to produce image quality enhanced virtual non-contrast images. The neural network is trained with training spectral data and training non-contrast-enhanced images generated from a non-contrast-enhanced scan. The spectral imaging system further includes a processor (132) configured to process the spectral data with the trained neural network to produce the image quality enhanced virtual non-contrast images.

Abstract: A device (10) for performing an amyloid assessment includes a radiation detector assembly (12) including at least one radiation detector (14). At least one electronic processor (20) is programmed to: detect radiation counts over a data acquisition time interval using the radiation detector assembly; compute at least one current count metric from the detected radiation counts; store the at least one current count metric associated with a current test date in a non-transitory storage medium (26); and determine an amyloid metric based on a comparison of the at least one current count metric with a count metric stored in the non-transitory storage medium associated with an earlier test date.

Abstract: A system (100) includes a computer readable storage medium (122) with computer executable instructions (124), including: a biophysical simulator component (126) configured to determine a fractional flow reserve value via simulation and a traffic light engine (128) configured to track a user-interaction with the computing system at one or more points of the simulation to determine the fractional flow reserve value. A processor (120) is configured to execute the biophysical simulator component to determine the fractional flow reserve value and configured to execute the traffic light engine to track the user-interaction with respect to determining the fractional flow reserve value and provide a warning in response to determining there is a potential incorrect interaction. A display is configured to display the warning requesting verification to proceed with the simulation from the point, wherein the simulation is resumed only in response to the processor receiving the requested verification.

Abstract: A non-spectral computed tomography scanner (102) includes a radiation source (112) configured to emit x-ray radiation, a detector array (114) configured to detect x-ray radiation and generate non-spectral data, and a memory (134) configured to store a spectral image module (130) that includes computer executable instructions including a neural network trained to produce spectral volumetric image data. The neural network is trained with training spectral volumetric image data and training non-spectral data. The non-spectral computed tomography scanner further includes a processor (126) configured to process the non-spectral data with the trained neural network to produce spectral volumetric image data.

Abstract: A non-transitory storage medium storing instructions readable and executable by an imaging workstation (18) including at least one electronic processor (20) to perform an image reconstruction method (100). The method includes: receiving emission imaging data (22) from an image acquisition device (12) wherein the emission imaging data has been filtered using an acquisition energy passband (18); generating filtered imaging data by filtering the emission imaging data with a second energy passband (90) that is narrower than an acquisition energy passband; reconstructing the filtered imaging data to generate an intermediate image; estimating one or more scatter correction factors (SCFs) from the intermediate image; and reconstructing the emission imaging data corrected with the estimated SCFs to generate a reconstructed image.

Abstract: A non-transitory computer-readable medium storing instructions readable and executable by a workstation (18) including at least one electronic processor (20) to perform a quality control (QC) method (100). The method includes: receiving a current QC data set acquired by a pixelated detector (14) and one or more prior QC data sets acquired by the pixelated detector; determining stability levels of detector pixels (16) of the pixelated detector over time from the current QC data set and the one or more prior QC data sets; labeling a detector pixel of the pixelated detector as dead when the stability level determined for the detector pixel is outside of a stability threshold range; and displaying, on a display device (24) operatively connected with the workstation, an identification (28) of the detector pixels labelled as dead.

Abstract: A device (10) for performing an amyloid assessment includes a radiation detector assembly (12) including at least one radiation detector (14). At least one electronic processor (20) is programmed to: detect radiation counts over a data acquisition time interval using the radiation detector assembly; compute at least one current count metric from the detected radiation counts; store the at least one current count metric associated with a current test date in a non-transitory storage medium (26); and determine an amyloid metric based on a comparison of the at least one current count metric with a count metric stored in the non-transitory storage medium associated with an earlier test date.

Abstract: A non-transitory computer-readable medium stores instructions readable and executable by a mobile device (32) with a display (34) and including at least one electronic processor (35) to perform a patient appointment timeline tracking method (100, 200). The method includes: receiving, via a wireless communication path (36), information at the mobile device about a patient appointment at a medical facility including estimated time information for events in the patient appointment; controlling the display to display a timeline (40) of the events in the patient appointment, the events being displayed as icons (42), the displayed time-line including the time information for the events; detecting, via one or more user inputs, a selection of one of the icons; and in response to detecting the user inputs, controlling the display to present information related to the selected icon.

Abstract: A detector array (112) includes a detector pixel (206). The detector pixel includes a three dimensional cavity (304 and 306; 432 and 404) having walls (308/602 and 316; 434 and 406/502) that include active regions, which detect light photons traversing within the three dimensional cavity and produce respective electrical signals indicative thereof. The detector pixel further includes a first scintillator (320; 410) disposed in the three dimensional cavity adjacent to a bottom (320; 416) of the at least one detector pixel. The detector pixel further includes a second scintillator (326; 444) disposed in the three dimensional cavity on top of the first scintillator, wherein the first and second scintillators emits the light photons in response to absorbing x-ray photons. At least one of the walls is vertically oriented with respect to detector pixel, maximizing contact area between a corresponding active region and one of the first or second scintillators.

Abstract: A system (100) for reconstruction of medical images over a network comprises a scheduler (302) that schedules a reconstruction request (108) and the reconstruction request includes a medical image reconstruction of a subject according to an imaging protocol The scheduling includes scheduling of a plurality of events, each event with a corresponding time, and the plurality of events include at least one event with the corresponding time selected from a group consisting of a first time (520) to transmit raw image data (114) over a first network from a source node (116) to a reconstruction node (106), a second time (522) to reconstruct the medical image (118) by the reconstruction node, and a third time (524) to transmit the reconstructed medical image over a second network from the reconstruction node to a destination node (120).

Abstract: A non-spectral computed tomography scanner (102) includes a radiation source (112) configured to emit x-ray radiation, a detector array (114) configured to detect x-ray radiation and generate non-spectral data, and a memory (134) configured to store a spectral image module (130) that includes computer executable instructions including a neural network trained to produce spectral volumetric image data. The neural network is trained with training spectral volumetric image data and training non-spectral data. The non-spectral computed tomography scanner further includes a processor (126) configured to process the non-spectral data with the trained neural network to produce spectral volumetric image data.

Abstract: A non-transitory storage medium storing instructions readable and executable by an imaging workstation (18) including at least one electronic processor (20) to perform an image reconstruction method (100). The method includes: receiving emission imaging data (22) from an image acquisition device (12) wherein the emission imaging data has been filtered using an acquisition energy passband (18); generating filtered imaging data by filtering the emission imaging data with a second energy passband (90) that is narrower than an acquisition energy passband; reconstructing the filtered imaging data to generate an intermediate image; estimating one or more scatter correction factors (SCFs) from the intermediate image; and reconstructing the emission imaging data corrected with the estimated SCFs to generate a reconstructed image.

Abstract: A system (1) includes a device (12, 116 or 118) with memory with spectral volumetric image data generated by a spectrally configured computed tomography scanner including a radiation source and a radiation detector and an image guided system (14) configured to employ the spectral volumetric image data for an image guided procedure. A computer readable medium is encoded with computer executable instructions, where the computer executable instructions, when executed by a processor, causes the processor to: obtain spectral volumetric image data generated by a spectrally configured computed tomography scanner including a radiation source and a radiation detector, and employ the spectral volumetric image data for an image guided procedure. A method includes receiving spectral volumetric image data generated by a spectrally configured computed tomography scanner including a radiation source and a radiation detector, and utilizing he spectral volumetric image data for an image guided procedure.

Abstract: A spectral computed tomography imaging system (102) includes a radiation source (112) configured to emit x-ray radiation and a detector array (114) configured to detect x-ray radiation and generate spectral data. The spectral imaging system further includes a memory (134) configured to store a virtual non-contrast image enhancing module (136) that includes computer executable instructions including a neural network trained to produce image quality enhanced virtual non-contrast images. The neural network is trained with training spectral data and training non-contrast-enhanced images generated from a non-contrast-enhanced scan. The spectral imaging system further includes a processor (132) configured to process the spectral data with the trained neural network to produce the image quality enhanced virtual non-contrast images.

Abstract: An imaging system includes an X-ray tube (202) having a focal spot (204) and a port window (206), and a filter (208) having at least a first region (310) with a first material having first X-ray attenuation characteristics for a redetermined X-ray photon energy range of interest and a second region (312) with a different X-ray attenuation characteristic. The filter is disposed between the port window and an examination region (108) and is configured to rotate such that the at least the first and the second regions sweep through and filter X-ray radiation emitted from the focal spot. The system further includes an X-ray radiation flux detector (2802, 2902) configured to detect an X-ray radiation flux of the filtered X-ray radiation, a detector array (112) configured to detect the filtered X-ray radiation traversing the examination region and produce a signal indicative thereof, and a reconstructor (114) configured to process the signal based on the detected flux to reconstruct volumetric image data.

Abstract: A non-transitory computer-readable medium storing instructions readable and executable by a workstation (18) including at least one electronic processor (20) to perform a quality control (QC) method (100). The method includes: receiving a current QC data set acquired by a pixelated detector (14) and one or more prior QC data sets acquired by the pixelated detector; determining stability levels of detector pixels (16) of the pixelated detector over time from the current QC data set and the one or more prior QC data sets; labeling a detector pixel of the pixelated detector as dead when the stability level determined for the detector pixel is outside of a stability threshold range; and displaying, on a display device (24) operatively connected with the workstation, an identification (28) of the detector pixels labelled as dead.

Abstract: A medical imaging subject support table includes a belt conveyor system with a conveyor belt (18) maintained in tension and passing through a bore (14) of an imaging device (12); and motorized pulleys (20) disposed at opposite ends of the bore to move the conveyor belt through the bore. Table supports (24) are positioned outside of the bore of the imaging device on opposite ends of the bore and support the conveyor belt outside the bore of the imaging device.

Abstract: A system (100) includes a computer readable storage medium (122) with computer executable instructions (124), including: a biophysical simulator component (126) configured to determine a fractional flow reserve value via simulation and a traffic light engine (128) configured to track a user-interaction with the computing system at one or more points of the simulation to determine the fractional flow reserve value. A processor (120) is configured to execute the biophysical simulator component to determine the fractional flow reserve value and configured to execute the traffic light engine to track the user-interaction with respect to determining the fractional flow reserve value and provide a warning in response to determining there is a potential incorrect interaction. A display is configured to display the warning requesting verification to proceed with the simulation from the point, wherein the simulation is resumed only in response to the processor receiving the requested verification.

Abstract: A nuclear imaging chain (100) includes a molecular agent (102), an acquisition system (104), a reconstruction system (106), a detection system (108), and a display system (110). The various components of the imaging chain are optimized according to desired optimization criteria. The optimized characteristics of the imaging chain (100) may include one or more an agent characteristic, an acquisition characteristic (127), a reconstruction characteristic (143), a detection characteristic (159), and a display characteristic.

Abstract: A method includes receiving a signal indicative of a single user selected imaging protocol for scanning a patient. The imaging protocol includes parameters for two or more of a bone mineral density, a fat composition, or an aortic calcium imaging procedures. The method further includes performing a single scan of the patient using the single user selected protocol. The method further includes generating a single set of image data for the two or more of a bone mineral density, a fat composition, or an aortic calcium imaging procedures.