Full dose PET image estimation from low-dose PET imaging using deep learning

    公开(公告)号:US11576628B2

    公开(公告)日:2023-02-14

    申请号:US16959289

    申请日:2018-12-26

    摘要: Emission imaging data are reconstructed to generate a low dose reconstructed image. Standardized uptake value (SUV) conversion (30) is applied to convert the low dose reconstructed image to a low dose SUV image. A neural network (46, 48) is applied to the low dose SUV image to generate an estimated full dose SUV image. Prior to applying the neural network the low dose reconstructed image or the low dose SUV image is filtered using a low pass filter (32). The neural network is trained on a set of training low dose SUV images and corresponding training full dose SUV images to transform the training low dose SUV images to match the corresponding training full dose SUV images, using a loss function having a mean square error loss component (34) and a loss component (36) that penalizes loss of image texture and/or a loss component (38) that promotes edge preservation.

    Correction method for quantification accuracy improvement in list mode reconstruction

    公开(公告)号:US11428829B2

    公开(公告)日:2022-08-30

    申请号:US16963320

    申请日:2019-01-30

    IPC分类号: G01T1/29 G01T1/161 G01T1/17

    摘要: 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) to reconstruct list mode data acquired over a frame acquisition time using a plurality of radiation detectors (17) in which the events of the list mode data is timestamped. The method includes: for the sub-frame bins of a plurality of sub-frame bins into which the frame acquisition time is divided, determining a sub-frame singles rates map for the plurality of radiation detectors from the list mode data whose time stamps reside in the sub-frame bin; determining a singles rate for the singles events of the list mode data using the sub-frame singles rates maps wherein the singles rates for the singles events are determined at a temporal resolution that is finer than the frame acquisition time; determining correction factors for the list mode data using the determined singles rates for the singles events of the list mode data; and reconstructing the list mode data of the frame acquisition time using the determined correction factors to generate a reconstructed image for the frame acquisition time.

    Iterative image reconstruction with dynamic suppression of formation of noise-induced artifacts

    公开(公告)号:US11210820B2

    公开(公告)日:2021-12-28

    申请号:US16336562

    申请日:2017-09-25

    IPC分类号: G06T7/136 G06T11/00

    摘要: 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.

    Heart segmentation methodology for cardiac motion correction

    公开(公告)号:US11138739B2

    公开(公告)日:2021-10-05

    申请号:US16349807

    申请日:2017-11-20

    IPC分类号: G06T7/12 G06T7/149

    摘要: A machine learning guided image segmentation process is performed by an electronic processor (10). Image segmentation (22) is performed to generate an initial segmented representation (50) of an anatomical structure in the medical image. Parameters of a geometric shape are fitted (52) to the anatomical structure in the medical image to produce initial fitted shape parameters (54). A classification is assigned for the anatomical structure in the medical image using at least one classifier (60) operating on the initial fitted shape parameters and the initial segmented representation of the anatomical structure. A final segmented representation (72) of the anatomical structure in the medical image is generated by operations including repeating (70) the image segmentation using the classification as prior knowledge. In illustrative embodiments, the anatomical structure is a heart and the geometric shape is an ellipsoid.

    Hybrid TOF and non-TOF PET systems with joint TOF and non-TOF image reconstruction

    公开(公告)号:US11061151B2

    公开(公告)日:2021-07-13

    申请号:US16466587

    申请日:2017-12-04

    IPC分类号: G01T1/29 A61B6/03 A61B6/00

    摘要: 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.