Abstract: A non-transitory storage medium stores instructions readable and executable by an imaging workstation (14) including at least one electronic processor (16) operatively connected with a display device (20) to perform an image reconstruction method (100). The method includes: reconstructing imaging data acquired by an image acquisition device (12) using an iterative image reconstruction algorithm to generate at least one reconstructed image (22); delineating one or more contours (26) of the at least one reconstructed image to determine a region of interest (ROI) (24) of the at least one reconstructed image; computing at least one quality metric value (30) of the ROI, the at least one quality metric value including at least one of a convergence quality metric, a partial volume effect (PVE) quality metric, and a local count quality metric; and displaying, on the display device, the at least one quality metric value and the at least one reconstructed image showing the ROI.

Abstract: An imaging device (1) includes a positron emission tomography (PET) scanner (10) including radiation detectors (12) and coincidence circuitry for detecting electron-positron annihilation events as 511 keV gamma ray pairs defining lines of response (LORs) with each event having a detection time difference At between the 511 keV gamma rays of the pair. At least one processor (30) is programmed to reconstruct a dataset comprising detected electron-positron annihilation events acquired for a region of interest by the PET scanner to form a reconstructed PET image wherein the reconstruction includes TOF localization of the events along respective LORs using a TOF kernel having a location parameter dependent on At and a TOF kernel width or shape that varies over the region of interest. A display device (34) is configured to display the reconstructed PET image.

Abstract: Image processing performed by a computer (22) includes iterative image reconstruction or refinement (26, 56) that produces a series of update images ending in an iteratively reconstructed or refined image. A difference image (34, 64) is computed between a first update image (30, 60) and a second update image (32, 62) of the series. The difference image is converted to a feature image (40) and is used in the iterative processing (26, 56) or in post-processing (44) performed on the iteratively reconstructed or refined images or images from different reconstruction or refinement techniques. In another embodiment, first and second image reconstructions (81, 83) are performed to generate respective first and second reconstructed images (80, 82). A difference image (84) is computed between two images each selected from the group: the first reconstructed image, an update image of the first reconstruction, the second reconstructed image, and an update image of the second reconstruction.

Abstract: A diagnostic imaging system retrieves data (206) from a plurality of accessible data sources, the accessible data sources storing data including physiological data describing a subject to be imaged, a nature of a requested diagnostic image, image preferences of a clinician who requested the diagnostic image, and previously reconstructed images of the requested nature of the subject and/or other subjects, reconstruction parameters and/or sub-routines used to reconstruct the previously reconstructed images. The system analyzes (6, 12) the retrieved data to automatically generate reconstruction parameters and/or sub-steps specific to the nature of the requested diagnostic image, the subject, and the clinician image preferences. The system controls a display device (10, 216) to display the generated reconstruction parameters and/or sub-routines to the user for a user selection.

Abstract: A diagnostic imaging system retrieves data (206) from a plurality of accessible data sources, the accessible data sources storing data including physiological data describing a subject to be imaged, a nature of a requested diagnostic image, image preferences of a clinician who requested the diagnostic image, and previously reconstructed images of the requested nature of the subject and/or other subjects, reconstruction parameters and/or sub-routines used to reconstruct the previously reconstructed images. The system analyzes (6, 12) the retrieved data to automatically generate reconstruction parameters and/or sub-steps specific to the nature of the requested diagnostic image, the subject, and the clinician image preferences. The system controls a display device (10, 216) to display the generated reconstruction parameters and/or sub-routines to the user for a user selection.

Abstract: In a multi-session imaging study, information from a previous imaging session is stored in a Binary Large Object (BLOB). Current emission imaging data are reconstructed into a non-attenuation corrected (NAC) current emission image. A spatial transform is generated aligning a previous NAC emission image from the BLOB to the current NAC emission image. A previous computed tomography (CT) image from the BLOB is warped using the spatial transform, and the current emission imaging data are reconstructed with attenuation correction using the warped CT image. Alternatively, low dose current emission imaging data and a current CT image are acquired, a spatial transform is generated aligning the previous CT image to the current CT image, a previous attenuation corrected (AC) emission image from the BLOB is warped using the spatial transform, and the current emission imaging data are reconstructed using the current CT image with the warped AC emission image as prior.

Abstract: A medical imaging system (10) comprises one or more displays (66). A viewer device (86) generates an interactive user interface screen (80) on the display (66), which viewer device (86) enables a user to simultaneously inspect selected image data of multiple patients or multiple images.

Abstract: Method and apparatus are disclosed for generating a scatter-corrected image from positron emission tomography (PET) or other radioemission imaging data (20) acquired of an object (12) in a field of view (14). A background portion (26B) of the PET imaging data is identified corresponding to a background region (14B) of the FOV that is outside of the object. An outside-FOV activity estimate (40) for at least one spatial region outside of the FOV and into which the object extends is adjusted (e.g. iterative or several randomly selected estimates) to optimize a simulated scatter distribution for the combination of the PET imaging data and the outside FOV activity estimate to match the background portion (26B) of the PET imaging data. The PET imaging data are reconstructed to generate a scatter-corrected PET image of the object in the FOV using the optimized simulated scatter distribution.

Abstract: Method and apparatus are disclosed for generating a scatter-corrected image from positron emission tomography (PET) or other radioemission imaging data (20) acquired of an object (12) in a field of view (14). A background portion (26B) of the PET imaging data is identified corresponding to a background region (14B) of the FOV that is outside of the object. An outside-FOV activity estimate (40) for at least one spatial region outside of the FOV and into which the object extends is adjusted (e.g. iterative or several randomly selected estimates) to optimize a simulated scatter distribution for the combination of the PET imaging data and the outside FOV activity estimate to match the background portion (26B) of the PET imaging data. The PET imaging data are reconstructed to generate a scatter-corrected PET image of the object in the FOV using the optimized simulated scatter distribution.

Abstract: A diagnostic imaging system retrieves data (206) from a plurality of accessible data sources, the accessible data sources storing data including physiological data describing a subject to be imaged, a nature of a requested diagnostic image, image preferences of a clinician who requested the diagnostic image, and previously reconstructed images of the requested nature of the subject and/or other subjects, reconstruction parameters and/or sub-routines used to reconstruct the previously reconstructed images. The system analyzes (6, 12) the retrieved data to automatically generate reconstruction parameters and/or sub-steps specific to the nature of the requested diagnostic image, the subject, and the clinician image preferences. The system controls a display device (10, 216) to display the generated reconstruction parameters and/or sub-routines to the user for a user selection.

Abstract: A method and system for removing an object support from imaging data such as CT imaging data are provided. The automatic or semi-automatic removal process comprises identifying and locating the top edge of the object support in sagittal imaging plane data, and then removing the object support from transverse or volumetric imaging data.

Abstract: A medical imaging system (10) comprises one or more displays (66). A viewer device (86) generates an interactive user interface screen (80) on the display (66), which viewer device (86) enables a user to simultaneously inspect selected image data of multiple patients or multiple images.

Abstract: An image display method comprises: color coding a second image respective to an intensity spectrum with a portion or portions of the intensity spectrum set to be transparent to generate a color coded second image; combining a first image and the color coded second image to generate a fused image; and displaying the fused image. An image display system comprises: an image generating module configured to generate an image by color coding an input image in accordance with a colormap assigning colors to intensities of an intensity spectrum; a colormap modifying module configured to select a portion of the intensity spectrum to be transparent; and a display configured to display the generated image.

Abstract: In image registration, a similarity measure is computed of first and second images (4, 6) offset at a plurality of relative axial offsets (30). A starting relative axial offset (40) between the first and second images is identified based on the computed similarity measures. An iterative image registration process is performed to relatively register the first and second images (4, 6) using the identified starting relative axial offset between the first and second images as an initial condition for the iterative image registration process. A starting relative in-slice offset (42) may also be identified as an in-slice offset effective to align corresponding slices of the first and second images (4, 6) offset at the starting relative axial offset (40), the identified starting relative in-slice offset also being used as an initial condition for the iterative image registration process.

Abstract: A method and system for removing an object support from imaging data such as CT imaging data are provided. The automatic or semi-automatic removal process comprises identifying and locating the top edge of the object support in sagittal imaging plane data, and then removing the object support from transverse or volumetric imaging data.

Abstract: A medical imaging system (10) comprises one or more displays (66). A viewer device (86) generates an interactive user interface screen (80) on the display (66), which viewer device (86) enables a user to simultaneously inspect selected image data of multiple patients or multiple images.

Abstract: A medical imaging system (10) comprises one or more displays (66). A viewer device (86) generates an interactive user interface screen (80) on the display (66), which viewer device (86) enables a user to simultaneously inspect selected image data of multiple patients or multiple images.

Abstract: A medical imaging system (10) comprises one or more displays (66). A viewer device (86) generates an interactive user interface screen (80) on the display (66), which viewer device (86) enables a user to simultaneously inspect selected image data of multiple patients or multiple images.

Abstract: An image display method comprises: color coding a second image respective to an intensity spectrum with a portion or portions (72, 82, 92) of the intensity spectrum set to be transparent to generate a color coded second image; combining a first image and the color coded second image to generate a fused image; and displaying the fused image. An image display system comprises: an image generating module (50) configured to generate an image by color coding an input image in accordance with a colormap (52) assigning colors to intensities of an intensity spectrum; a colormap modifying module (56) configured to select a portion (72, 82, 92) of the intensity spectrum to be transparent; and a display (42) configured to display the generated image.

Abstract: In image registration, a similarity measure is computed of first and second images (4, 6) offset at a plurality of relative axial offsets (30). A starting relative axial offset (40) between the first and second images is identified based on the computed similarity measures. An iterative image registration process is performed to relatively register the first and second images (4, 6) using the identified starting relative axial offset between the first and second images as an initial condition for the iterative image registration process. A starting relative in-slice offset (42) may also be identified as an in-slice offset effective to align corresponding slices of the first and second images (4, 6) offset at the starting relative axial offset (40), the identified starting relative in-slice offset also being used as an initial condition for the iterative image registration process.