Abstract: A method includes calculating a sum of all samples at each projection view of a scan of an object, determining a maximum value of the calculated sums, averaging a plurality of samples m at a projection view index k when the sum of all samples at index k is less than a predetermined percentage of the maximum value, comparing the average to a threshold t, determining the projection truncated when the average is greater than t, and determining the projection not truncated when the average is not greater than t.

Abstract: A system is provided for remotely servicing medical diagnostic systems. The diagnostic systems may include a range of modalities and system types. A remote service facility may be contacted by the diagnostic systems, or may contact the diagnostic systems via a network link. Service requests, messages, protocols, data and log files, and so forth, may be transmitted between the diagnostic systems and the service facility. The service requests are handled by the service facility interactively with the medical diagnostic systems. The diagnostic systems are thereby apprised of the status of service requests, service reports, and so forth. A uniform interface and platform are provided for facilitating interactive communications of service requests and data between the diagnostic systems and the service facility.

Abstract: A method for performing reference normalization for an image created by an imaging system. The imaging system includes a radiation detector array with a right and left edge. The method includes receiving a projection dataset created by the imaging system in response to a varying x-ray tube current. The projection dataset includes a view and predicted fluxes are calculated for the set of reference channels within the view. A right set of reference channels are located proximate at the right edge of the detector array and a left set of reference channels are located proximate to the left edge of the detector array. The method also includes calculating average actual fluxes for the sets of reference channels. Based on the predicted reference fluxes and the average fluxes, a reference correction value for the view is determined. The correction value is applied for the reference correction of the view.

Abstract: A method for generating a simulated patient image is disclosed. In an exemplary embodiment, the method includes obtaining image data from an actual patient image and generating simulated noise data. The image data is then combined with the simulated noise data to create the simulated patient image. In one aspect, scan data from the actual patient image is combined with the generated simulated noise data to create pre-image data, and the pre-image data is then reconstructed to create simulated image data. In another aspect, a set of individual noise pattern images for each a plurality of phantom objects is created. At least one of the individual noise pattern images is selected for combination with the actual patient image. The at least one selected individual noise pattern image is then combined with the actual patient image, thereby creating the simulated patient image.

Abstract: A method includes calculating a sum of all samples at each projection view of a scan of an object, determining a maximum value of the calculated sums, averaging a plurality of samples m at a projection view index k when the sum of all samples at index k is less than a predetermined percentage of the maximum value, comparing the average to a threshold t, determining the projection truncated when the average is greater than t, and determining the projection not truncated when the average is not greater than t.

Abstract: A method for generating a simulated patient image is disclosed. In an exemplary embodiment, the method includes obtaining image data from an actual patient image and generating simulated noise data. The image data is then combined with the simulated noise data to create the simulated patient image. In one aspect, scan data from the actual patient image is combined with the generated simulated noise data to create pre-image data, and the pre-image data is then reconstructed to create simulated image data. In another aspect, a set of individual noise pattern images for each a plurality of phantom objects is created. At least one of the individual noise pattern images is selected for combination with the actual patient image. The at least one selected individual noise pattern image is then combined with the actual patient image, thereby creating the simulated patient image.