DECORRELATION MECHANISM AND DUAL NECK AUTOENCODER FOR DEEP LEARNING

    公开(公告)号:US20230186055A1

    公开(公告)日:2023-06-15

    申请号:US18081156

    申请日:2022-12-14

    CPC classification number: G06N3/0455 G06N3/094

    Abstract: In one embodiment, there is provided a dual neck autoencoder module for reducing adversarial attack transferability. The dual neck autoencoder module includes an encoder module configured to receive input data; a decoder module; and a first bottleneck module and a second bottleneck module coupled, in parallel, between the encoder module and the decoder module. The decoder module is configured to generate a first estimate based, at least in part, on a first intermediate data set from the first bottleneck module, and a second estimate based, at least in part, on a second intermediate data set from the second bottleneck module. The first intermediate data set and the second intermediate data set are at least partially decorrelated based, at least in part, on a correlation loss.

    ROBOTIC ARM-BASED CLINICAL MICRO-CT SYSTEM AND METHOD

    公开(公告)号:US20230133386A1

    公开(公告)日:2023-05-04

    申请号:US17980948

    申请日:2022-11-04

    Abstract: In one embodiment, there is provided a micro-CT (computed tomography) apparatus. The micro-CT apparatus includes an x-ray source coupled to a source robotic arm, an x-ray detector coupled to a detector robotic arm, and a computing device. The computing device includes a data acquisition module and a reconstruction module. The data acquisition module is configured to acquire local scan data of a volume of interest (VOI) contained in an imaging object. The reconstruction module is configured to reconstruct an image of the VOI based, at least in part, on the local scan data, and based, at least in part, on background compensation data.

    Synergized pulsing-imaging network (SPIN)

    公开(公告)号:US11454690B2

    公开(公告)日:2022-09-27

    申请号:US16768834

    申请日:2018-12-07

    Inventor: Ge Wang Qing Lyu Tao Xu

    Abstract: A synergized pulsing-imaging network is described. A method of optimizing a magnetic resonance imaging (MRI) system includes optimizing, by a synergized pulsing-imaging network (SPIN) circuitry a pulse sequence based, at least in part, on a loss function associated with a reconstruction network. The method further includes optimizing, by the SPIN circuitry, the reconstruction network based, at least in part, on intermediate raw MRI data and based, at least in part, on a ground truth MRI image data. The intermediate raw MRI data is determined based, at least in part on the pulse sequence.

    Detection scheme for x-ray small angle scattering

    公开(公告)号:US11313814B2

    公开(公告)日:2022-04-26

    申请号:US16955939

    申请日:2018-12-20

    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 complementary 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 grating 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.

    Systems and methods for integrating tomographic image reconstruction and radiomics using neural networks

    公开(公告)号:US11049244B2

    公开(公告)日:2021-06-29

    申请号:US16621800

    申请日:2018-06-18

    Abstract: Computed tomography (CT) screening, diagnosis, or another image analysis tasks are performed using one or more networks and/or algorithms to either integrate complementary tomographic image reconstructions and radiomics or map tomographic raw data directly to diagnostic findings in the machine learning framework. One or more reconstruction networks are trained to reconstruct tomographic images from a training set of CT projection data. One or more radiomics networks are trained to extract features from the tomographic images and associated training diagnostic data. The networks/algorithms are integrated into an end-to-end network and trained. A set of tomographic data, e.g., CT projection data, and other relevant information from an individual is input to the end-to-end network, and a potential diagnosis for the individual based on the features extracted by the end-to-end network is produced. The systems and methods can be applied to CT projection data, MRI data, nuclear imaging data, ultrasound signals, optical data, other types of tomographic data, or combinations thereof.

    DEEP NEURAL NETWORK FOR CT METAL ARTIFACT REDUCTION

    公开(公告)号:US20210000438A1

    公开(公告)日:2021-01-07

    申请号:US16978258

    申请日:2019-03-06

    Abstract: A deep neural network for metal artifact reduction is described. A method for computed tomography (CT) metal artifact reduction (MAR) includes generating, by a projection completion circuitry, an intermediate CT image data based, at least in part, on input CT projection data. The intermediate CT image data is configured to include relatively fewer artifacts than an uncorrected CT image reconstructed from the input CT projection data. The method further includes generating, by an artificial neural network (ANN), CT output image data based, at least in part, on the intermediate CT image data. The CT output image data is configured to include relatively fewer artifacts compared to the intermediate CT image data. The method may further include generating, by detail image circuitry, detail CT image data based, at least in part, on input CT image data. The CT output image data is generated based, at least in part, on the detail CT image data.

    STATIONARY IN-VIVO GRATING-ENABLED MICRO-CT ARCHITECTURE (SIGMA)

    公开(公告)号:US20200261030A1

    公开(公告)日:2020-08-20

    申请号:US16761543

    申请日:2018-11-06

    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.

    X-optogenetics / U-optogenetics
    29.
    发明授权

    公开(公告)号:US10737111B2

    公开(公告)日:2020-08-11

    申请号:US14971777

    申请日:2015-12-16

    Abstract: Methods and systems for performing optogenetics using X-rays or ultrasound waves are provided. Visible-light-emitting nanophosphors can be provided to a sample, and X-ray stimulation can be used to stimulate the nanophosphors to emit visible light. Alternatively, ultrasonic waves can be provided to the sample to cause sonoluminescence, also resulting in emission of visible light, and this can be aided by the use of a chemiluminescent agent present in the sample. The emitted light can trigger changes in proteins that modulate membrane potentials in neuronal cells.

Patent Agency Ranking