NEURAL NETWORK FOR IMPROVED PERFORMANCE OF MEDICAL IMAGING SYSTEMS

    公开(公告)号:US20220327665A1

    公开(公告)日:2022-10-13

    申请号:US17225672

    申请日:2021-04-08

    Abstract: Existing, low quality images can be restored using reconstruction or a combination of post-reconstruction techniques to generate a real patient phantom. The real patient phantom (RPP) can then be simulated in Monte Carlo simulations of a higher performance system and a lower performance system. Alternatively, the RPP can be simulated in the higher performance system, and a real scan can be performed by an existing, lower performance system. The higher performance system can be differentiated from the lower performance system in a variety of ways, including a higher resolution time of flight measurement capability, a greater sensitivity, smaller detector crystals, or less scattering. A neural network can be trained using the images produce by the higher performance system as the target, and the images produced by the lower performance system as the input. After training, the trained neural network can be used to output input images taken in a lower performance system with higher performance system characteristics.

    PET RECONSTRUCTION FOR ADJUSTABLE PET SYSTEM

    公开(公告)号:US20240122558A1

    公开(公告)日:2024-04-18

    申请号:US17963737

    申请日:2022-10-11

    CPC classification number: A61B6/037 A61B6/4258 A61B6/481

    Abstract: A PET scanner includes gamma-ray detector rings that form a bore through which an imaging subject is translated, a length of the bore defining an axial length of the PET scanner, the gamma-ray detector rings being movable along the axial length, the gamma-ray detector rings including gamma-ray detector modules therein, and processing circuitry configured to receive PET data associated with a plurality of transaxial slices of the imaging subject, the PET data including a first set of spatial information and timing information corresponding to a first data acquisition period for the gamma-ray detector modules in a first axial position and a second set of spatial information and timing information corresponding to a second data acquisition period for the gamma-ray detector modules in a second axial position, and reconstruct a PET image based on the first set of spatial and timing information and the second set of spatial and timing information.

    APPARATUS AND METHOD FOR MEDICAL IMAGE RECONSTRUCTION USING DEEP LEARNING TO IMPROVE IMAGE QUALITY IN POSITRON EMISSION TOMOGRAPHY (PET)

    公开(公告)号:US20220110600A1

    公开(公告)日:2022-04-14

    申请号:US17554019

    申请日:2021-12-17

    Abstract: A deep learning (DL) convolution neural network (CNN) reduces noise in positron emission tomography (PET) images, and is trained using a range of noise levels for the low-quality images having high noise in the training dataset to produce uniform high-quality images having low noise, independently of the noise level of the input image. The DL-CNN network can be implemented by slicing a three-dimensional (3D) PET image into 2D slices along transaxial, coronal, and sagittal planes, using three separate 2D CNN networks for each respective plane, and averaging the outputs from these three separate 2D CNN networks. Feature-oriented training can be implemented by segmenting each training image into lesion and background regions, and, in the loss function, applying greater weights to voxels in the lesion region. Other medical images (e.g. MRI and CT) can be used to enhance resolution of the PET images and provide partial volume corrections.

    METHOD AND APPARATUS FOR SCATTER ESTIMATION IN POSITRON EMISSION TOMOGRAPHY

    公开(公告)号:US20210335023A1

    公开(公告)日:2021-10-28

    申请号:US16860425

    申请日:2020-04-28

    Abstract: The present disclosure relates to an apparatus for estimating scatter in positron emission tomography, comprising processing circuitry configured to acquire an emission map and an attenuation map, each representing an initial image reconstruction of a positron emission tomography scan, calculate, using a radiative transfer equation (RTE) method, a scatter source map of a subject of the positron emission tomography scan based on the emission map and the attenuation map, estimate, using the RTE method and based on the emission map, the attenuation map, and the scatter source map, scatter, and perform an iterative image reconstruction of the positron emission tomography scan based on the estimated scatter and raw data from the positron emission tomography scan of the subject.

    METHOD OF REGULARLIZATION DESIGN AND PARAMETER TUNING FOR DYNAMIC POSITRON EMISSION TOMOGRAPHY IMAGE RECONSTRUCTION

    公开(公告)号:US20210335022A1

    公开(公告)日:2021-10-28

    申请号:US16857916

    申请日:2020-04-24

    Abstract: A method of imaging includes obtaining a plurality of dynamic sinograms, each dynamic sinogram representing detection events of gamma rays at a plurality of detector elements, summing the plurality of dynamic sinograms to generate an activity map based on a radioactivity level of the gamma rays; reconstructing, using the plurality of dynamic sinograms, a plurality of dynamic images, each of the plurality of dynamic images corresponding to one of the each of the plurality of dynamic sinograms, and generating, using the plurality of dynamic sinograms and the activity map, at least one parametric image.

Patent Agency Ranking