Feature-based image processing using feature images extracted from different iterations

    公开(公告)号:US11049230B2

    公开(公告)日:2021-06-29

    申请号:US16325213

    申请日:2017-08-22

    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. A feature image is generated from the difference image and used to combine the first and second reconstructed images.

    Time-of-flight resolution-adaptive image regularization and filtering in positron emission tomography

    公开(公告)号:US11009615B2

    公开(公告)日:2021-05-18

    申请号:US16470730

    申请日:2017-12-18

    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 acquisition characteristics such as count rates or operating temperature of the detectors.

    Generation of accurate hybrid datasets for quantitative molecular imaging

    公开(公告)号:US11354832B2

    公开(公告)日:2022-06-07

    申请号:US16609890

    申请日:2018-05-01

    Abstract: A non-transitory computer readable medium storing instructions readable and executable by an imaging workstation (14) including at least one electronic processor (16) to perform a dataset generation method (100) operating on emission imaging data acquired of a patient for one or more axial frames at a corresponding one or more bed positions, the method comprising: (a) identifying a frame of interest from the one or more axial frames; (b) generating simulated lesion data by simulating emission imaging data for the frame of interest of at least one simulated lesion placed in the frame of interest; (c) generating simulated frame emission imaging data by simulating emission imaging data for the frame of interest of the patient; (d) determining a normalization factor comprising a ratio of the value of a quantitative metric for the simulated patient data and the value of the quantitative metric for the emission imaging data acquired of the same patient for the frame of interest; and (e) generating a hybrid data set comprising the emission imaging data acquired of the patient for the one or more axial frames at the corresponding one or more bed positions with the frame of interest replaced by a combination of the simulated lesion data scaled by the normalization factor and the emission imaging data acquired of the patient for the frame of interest.

    Scatter correction for positron emission tomography (PET)

    公开(公告)号:US11282242B2

    公开(公告)日:2022-03-22

    申请号:US16963343

    申请日:2019-01-24

    Abstract: A non-transitory computer-readable medium stores instructions readable and executable by a workstation (18) including at least one electronic processor (20) to perform an image reconstruction method (100). The method includes: generating, from received imaging data, a plurality of intermediate images reconstructed without scatter correction from data partitioned into different energy windows; generating a fraction of true counts and a fraction of scatter events in the generated intermediate images; generating a final reconstructed image from the intermediate images, the fraction of true counts in the intermediate images, and the fraction of scatter counts in the intermediate images; and at least one of controlling the non-transitory computer readable medium to store the final image and control a display device (24) to display the final image.

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