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    CT SUPER-RESOLUTION GAN CONSTRAINED BY THE IDENTICAL, RESIDUAL AND CYCLE LEARNING ENSEMBLE (GAN-CIRCLE)
    11.
    发明申请
    CT SUPER-RESOLUTION GAN CONSTRAINED BY THE IDENTICAL, RESIDUAL AND CYCLE LEARNING ENSEMBLE (GAN-CIRCLE) 有权

    公开(公告)号：US20220230278A1

    公开(公告)日：2022-07-21

    申请号：US17564728

    申请日：2021-12-29

    Applicant: RENSSELAER POLYTECHNIC INSTITUTE

    Inventor： Ge Wang ,  Chenyu You ,  Wenxiang Cong ,  Hongming Shan

    IPC: G06T3/40 ,  G06N3/04

    Abstract: A system for generating a high resolution (HR) computed tomography (CT) image from a low resolution (LR) CT image is described. The system includes a first generative adversarial network (GAN) and a second GAN. The first GAN includes a first generative neural network (G) configured to receive a training LR image dataset and to generate a corresponding estimated HR image dataset, and a first discriminative neural network (DY) configured to compare a training HR image dataset and the estimated HR image dataset. The second GAN includes a second generative neural network (F) configured to receive the training HR image dataset and to generate a corresponding estimated LR image dataset, and a second discriminative neural network (DX) configured to compare the training LR image dataset and the estimated LR image dataset. The system further includes an optimization module configured to determine an optimization function based, at least in part, on at least one of the estimated HR image dataset and/or the estimated LR image dataset. The optimization function contains at least one loss function. The optimization module is further configured to adjust a plurality of neural network parameters associated with at least one of the first GAN and/or the second GAN, to optimize the optimization function.

    Stationary in-vivo grating-enabled micro-CT architecture (sigma)
    12.
    发明授权
    Stationary in-vivo grating-enabled micro-CT architecture (sigma) 有权

    公开(公告)号：US11382574B2

    公开(公告)日：2022-07-12

    申请号：US16761543

    申请日：2018-11-06

    Applicant: RENSSELAER POLYTECHNIC INSTITUTE

    Inventor： Ge Wang ,  Wenxiang Cong ,  Qingsong Yang ,  Guang Li

    IPC: A61B6/03 ,  A61B6/00 ,  G01N23/041

    Abstract: A stationary in-vivo grating-enabled micro-CT (computed tomography) architecture (SIGMA) system includes CT scanner control circuitry and a number of imaging chains. Each imaging chain includes an x-ray source array, a phase grating, an analyzer grating and a detector array. Each imaging chain is stationary and each x-ray source array includes a plurality of x-ray source elements. Each imaging chain has a centerline, the centerlines of the number of imaging chains intersect at a center point and a first angle between the centerlines of a first adjacent pair of imaging chains equals a second angle between the centerlines of a second adjacent pair of imaging chains. A plurality of selected x-ray source elements of a first x-ray source array is configured to emit a plurality of x-ray beams in a multiplexing fashion.

    Rapid filtration methods for dual-energy X-ray CT
    13.
    发明授权
    Rapid filtration methods for dual-energy X-ray CT 有权

    公开(公告)号：US11337663B2

    公开(公告)日：2022-05-24

    申请号：US16092393

    申请日：2017-04-06

    Applicant: RENSSELAER POLYTECHNIC INSTITUTE

    Inventor： Ge Wang ,  Wenxiang Cong ,  Yan Xi

    IPC: A61B6/00 ,  A61B6/03

    Abstract: Systems and method for performing X-ray computed tomography (CT) that can improve spectral separation and decrease motion artifacts without increasing radiation dose are provided. The systems and method can be used with either a kVp-switching source or a single-kVp source. When used with a kVp-switching source, an absorption grating and a filter grating can be disposed between the X-ray source and the sample to be imaged. Relative motion of the filter and absorption gratings can by synchronized to the kVp switching frequency of the X-ray source. When used with a single-kVp source, a combination of absorption and filter gratings can be used and can be driven in an oscillation movement that is optimized for a single-kVp X-ray source. With a single-kVp source, the absorption grating can also be omitted and the filter grating can remain stationary.

    DETECTION SCHEME FOR X-RAY SMALL ANGLE SCATTERING
    14.
    发明申请
    DETECTION SCHEME FOR X-RAY SMALL ANGLE SCATTERING 有权

    公开(公告)号：US20210080409A1

    公开(公告)日：2021-03-18

    申请号：US16955939

    申请日：2018-12-20

    Applicant: RENSSELAER POLYTECHNIC INSTITUTE

    Inventor： Ge Wang ,  Guang Li ,  Wenxiang Cong

    IPC: G01N23/20008 ,  G01N23/201

    Abstract: A detection scheme for x-ray small angle scattering is described. An x-ray small angle scattering apparatus may include a first grating and a complementary second grating. The first grating includes a plurality of first grating cells. The complementarity second grating includes a plurality of second grating cells. The second grating is positioned relative to the first grating. A configuration of the first grating, a configuration of the second grating and the relative positioning of the gratings are configured to pass one or more small angle scattered photons and to block one or more Compton scattered photons and one or more main x-ray photons.

    3-D CONVOLUTIONAL AUTOENCODER FOR LOW-DOSE CT VIA TRANSFER LEARNING FROM A 2-D TRAINED NETWORK
    15.
    发明申请
    3-D CONVOLUTIONAL AUTOENCODER FOR LOW-DOSE CT VIA TRANSFER LEARNING FROM A 2-D TRAINED NETWORK 审中-公开

    公开(公告)号：US20200349449A1

    公开(公告)日：2020-11-05

    申请号：US16964388

    申请日：2019-01-24

    Applicant: RENSSELAER POLYTECHNIC INSTITUTE

    Inventor： Ge Wang ,  Hongming Shan ,  Wenxiang Cong

    IPC: G06N3/08 ,  G06T5/00 ,  G06T5/50 ,  G06N3/04

    Abstract: A 3-D convolutional autoencoder for low-dose CT via transfer learning from a 2-D trained network is described, A machine learning method for low dose computed tomography (LDCT) image correction is provided. The method includes training, by a training circuitry, a neural network (NN) based, at least in part, on two-dimensional (2-D) training data. The 2-D training data includes a plurality of 2-D training image pairs. Each 2-D image pair includes one training input image and one corresponding target output image. The training includes adjusting at least one of a plurality of 2-D weights based, at least in part, on an objective function. The method further includes refining, by the training circuitry, the NN based, at least in part, on three-dimensional (3-D) training data. The 3-D training data includes a plurality of 3-D training image pairs. Each 3-D training image pair includes a plurality of adjacent 2-D training input images and at least one corresponding target output image. The refining includes adjusting at least one of a plurality of 3-D weights based, at least in part, on the plurality of 2-D weights and based, at least in part, on the objective function. The plurality of 2-D weights includes the at least one adjusted 2-D weight.

    3-D convolutional autoencoder for low-dose CT via transfer learning from a 2-D trained network
    19.
    发明授权
    3-D convolutional autoencoder for low-dose CT via transfer learning from a 2-D trained network 有权

    公开(公告)号：US11580410B2

    公开(公告)日：2023-02-14

    申请号：US16964388

    申请日：2019-01-24

    Applicant: RENSSELAER POLYTECHNIC INSTITUTE

    Inventor： Ge Wang ,  Hongming Shan ,  Wenxiang Cong

    IPC: G06T5/00 ,  G06T5/50 ,  G06N3/088 ,  G06N3/04

    Abstract: A 3-D convolutional autoencoder for low-dose CT via transfer learning from a 2-D trained network is described, A machine learning method for low dose computed tomography (LDCT) image correction is provided. The method includes training, by a training circuitry, a neural network (NN) based, at least in part, on two-dimensional (2-D) training data. The 2-D training data includes a plurality of 2-D training image pairs. Each 2-D image pair includes one training input image and one corresponding target output image. The training includes adjusting at least one of a plurality of 2-D weights based, at least in part, on an objective function. The method further includes refining, by the training circuitry, the NN based, at least in part, on three-dimensional (3-D) training data. The 3-D training data includes a plurality of 3-D training image pairs. Each 3-D training image pair includes a plurality of adjacent 2-D training input images and at least one corresponding target output image. The refining includes adjusting at least one of a plurality of 3-D weights based, at least in part, on the plurality of 2-D weights and based, at least in part, on the objective function. The plurality of 2-D weights includes the at least one adjusted 2-D weight.

    Energy-sensitive multi-contrast cost-effective CT system
    20.
    发明授权
    Energy-sensitive multi-contrast cost-effective CT system 有权

    公开(公告)号：US11266363B2

    公开(公告)日：2022-03-08

    申请号：US15999466

    申请日：2017-02-17

    Applicant: RENSSELAER POLYTECHNIC INSTITUTE

    Inventor： Ge Wang ,  Wenxiang Cong

    IPC: A61B6/00 ,  A61B6/04 ,  A61B6/03

    Abstract: Systems and methods for obtaining scattering images during computed tomography (CT) imaging are provided. Two gratings or grating layers can be disposed between the object to be imaged and the detector, and the gratings or grating layers can be arranged such that primary X-rays are blocked while scattered X-rays that are deflected as they pass through the object to be imaged reach the detector to generate the scattering image.

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