Abstract: In positron emission tomography (PET) imaging, PET imaging data (22) having TOF localization is reconstructed. TOF image reconstruction (30) is performed on the PET imaging data to produce a TOF reconstructed image (32). The TOF image reconstruction utilizes the TOF localization of the PET imaging data. Non-TOF image reconstruction (40) is also performed on the PET imaging data to produce a non-TOF reconstructed image (42). The non-TOF image reconstruction does not utilize the TOF localization of the PET imaging data. A comparison image (50) is computed which is indicative of differences between the TOF reconstructed image and the non TOF reconstructed image. An adjustment (54) is determined for the TOF image reconstruction based on the comparison image, such as alignment correction of an attenuation map (18), and the TOF image reconstruction is repeated on the PET imaging data with the determined adjustment to produce an adjusted TOF reconstructed image.

Abstract: A positron emission tomography (PET) detector array includes an enclosing radiation detector array (10) comprising radiation detector elements (14, 16) effective for detecting 511 keV radiation emanating from inside the radiation detector array. The radiation detector pixels of the cylindrical radiation detector array include both higher speed radiation detector elements (14) and lower speed radiation detector elements (16). The lower speed radiation detector pixels have a temporal resolution that is coarser than a temporal resolution of the higher speed radiation detector pixels.

Abstract: A time of flight (TOF) positron emission tomography (PET) image (38) is generated from TOF PET imaging data (10) acquired of a subject using a TOF PET imaging data acquisition device (6). Iterative image reconstruction (30) of the TOF PET imaging data is performed with TOF localization of counts along respective lines of response (LORs) to iteratively update a reconstructed image (32). Values for at least one regularization or filtering parameter are assigned to the TOF PET imaging data or to voxels of the reconstructed image based on an estimated TOF localization resolution for the TOF PET imaging data or voxels. Regularization (34) or filtering (36) of the reconstructed image is performed using the assigned values for the at least one regularization or filtering parameter. In some embodiments, the varying TOF localization resolution for the TOF PET imaging data or voxels is estimated based on related N acquisition characteristics such as count rates or operating temperature of the detectors.

Abstract: A nuclear medicine image reconstruction method generates a reconstructed image (44) by performing iterative image in reconstruction (30, 130) on nuclear medicine imaging data (22). The iterative image reconstruction produces a sequence of update images (34, 36, 134, 136). During the iterative image reconstruction, a standardized uptake value (SUV) transform (40) is applied to convert an update image (34, 36) to an update SUV image (42, 46). The SUV transform scales values of voxels of the update image to SUV values using scaling factors including at least a body size metric and a dose metric. During the iterative image reconstruction, at least one parameter used in an image update of the iterative image reconstruction is adjusted using the update SUV image. For example, a parameter of a prior or filter (38) incorporated into an image reconstruction update step (32) or used in filtering of an update image (36) may be adjusted.

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: Iterative reconstruction (20) of imaging data is performed to generate a sequence of update images (22) terminating at a reconstructed image. During the iterative reconstruction, at least one of an update image and a parameter of the iterative reconstruction is adjusted using an adjustment process separate from the iterative reconstruction. In some embodiments using an edge-preserving regularization prior (26), the adjustment process (30) adjusts an edge preservation threshold to reduce gradient steepness above which edge preservation applies for later iterations compared with earlier iterations. In some embodiments, the adjustment process includes determining (36, 38) for each pixel, voxel, or region of a current update image whether its evolution prior to the current update image 22) satisfies an artifact feature criterion. A local noise suppression operation (40) is performed on the pixel, voxel, or region if the evolution satisfies the artifact feature criterion and is not performed otherwise.

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: 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 radioemission scanner (12) is operated to acquire tomographic radioemission data of a radiopharmaceutical in a subject in an imaging field of view (FOV). An imaging system is operated to acquire extension imaging data of the subject in an extended FOV disposed outside of and adjacent the imaging FOV along an axial direction (18). A distribution of the radiopharmaceutical in the subject in the extended FOV is estimated based on the extension imaging data, and further based on a database (32) of reference subjects. The tomographic radioemission data are reconstructed to generate a reconstructed image (26) of the subject in the imaging FOV. The reconstruction includes correcting the reconstructed image for scatter from the extended FOV into the imaging FOV based on the estimated distribution of the radiopharmaceutical in the subject in the extended FOV.

Abstract: A system includes a compressor and a control system. The control system includes a processor and associated memory. The control system is configured to receive feedback comprising a thermodynamic characteristic or a mechanical characteristic of the compressor. Also, the control system is configured to generate an indication of a surge event or a stall event in the compressor based on the feedback.

Abstract: A system includes a compressor and a control system. The control system includes a processor and associated memory. The control system is configured to receive feedback comprising a thermodynamic characteristic or a mechanical characteristic of the compressor. Also, the control system is configured to generate an indication of a surge event or a stall event in the compressor based on the feedback.