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    PROVIDING A 3D RESULTS DATA SET
    1.
    发明公开
    PROVIDING A 3D RESULTS DATA SET 审中-公开

    公开(公告)号：US20240362833A1

    公开(公告)日：2024-10-31

    申请号：US18635226

    申请日：2024-04-15

    申请人： Siemens Healthineers AG

    发明人： Oliver Hornung ,  Michael Manhart ,  Markus Kowarschik ,  Manuela Meier

    IPC分类号： G06T11/00 ,  G06T7/00

    CPC分类号： G06T11/003 ,  G06T7/0012 ,  G06T2207/10116 ,  G06T2207/20084

    摘要： A computer-implemented method for providing a three-dimensional (3D) results data set includes: acquiring projection maps of an object under examination which are captured from various projection directions by a medical X-ray device; providing an initial projection matrix based on a static model of the X-ray device; providing a further projection matrix by applying a trained function to input data, wherein the input data is based on the initial projection matrix and the projection maps, wherein at least one parameter of the trained function is adapted based on an image quality metric and/or a consistency metric, and wherein the further projection matrix is provided as output data of the trained function; and providing the 3D results data set through reconstruction from the projection maps by the further projection matrix.

    DUAL-DOMAIN SELF-SUPERVISED LEARNING FOR ACCELERATED NON-CARTESIAN MAGNETIC RESONANCE IMAGING RECONSTRUCTION
    4.
    发明公开
    DUAL-DOMAIN SELF-SUPERVISED LEARNING FOR ACCELERATED NON-CARTESIAN MAGNETIC RESONANCE IMAGING RECONSTRUCTION 审中-公开

    公开(公告)号：US20240290011A1

    公开(公告)日：2024-08-29

    申请号：US18597629

    申请日：2024-03-06

    申请人： Hyperfine, Inc.

    发明人： Bo Zhou ,  Jo Schlemper ,  Neel Dey ,  Michal Sofka

    IPC分类号： G06T11/00

    CPC分类号： G06T11/003

    摘要： Systems and methods for dual-domain self-supervised learning for accelerated non-Cartesian magnetic resonance imaging reconstruction are provided. The present techniques provide a method for training a machine-learning model that receives magnetic resonance (MR) data and generates a reconstruction of the MR data. The machine-learning model can be trained based on a set of losses comprising a first loss value corresponding to a frequency-domain and a second loss value corresponding to an image-based domain. The training process can be a self-supervised training process that can utilize under-sampled and non-Cartesian MR data. The machine-learning model is trained by optimizing both data consistency in the frequency domain and appearance consistency in the image-based domain.

    Energy weighting of photon counts for conventional imaging
    5.
    发明授权
    Energy weighting of photon counts for conventional imaging 有权

    公开(公告)号：US12073491B2

    公开(公告)日：2024-08-27

    申请号：US17312036

    申请日：2019-12-09

    申请人： KONINKLIJKE PHILIPS N.V.

    发明人： Heiner Daerr ,  Artur Sossin

    IPC分类号： G01T1/36 ,  A61B6/03 ,  A61B6/42 ,  A61B6/58 ,  G01T1/24 ,  G06T11/00

    CPC分类号： G06T11/003 ,  A61B6/4241 ,  A61B6/585 ,  G01T1/24 ,  G06T2200/24 ,  G06T2207/10116

    摘要： A System for image processing, comprising an input interface (IN) for receiving energy resolved count data generated by a photon-counting detector (PCD) with at least 2 energy bin but preferable more than two. A count data transformer (DT) of the system is configured to perform a transformation operation to transform the energy resolved count data into transformed count data, the operation including applying one or more weights to the count data, the weights previously obtained based on i) calibration image data for the or a photon-counting detector and ii) calibration image data for an energy integrating detector. A data convertor component (CC) is configured to convert the transformed count data into through-material path length data. The system allows emulating an energy integrating detector.

    Imaging apparatus and imaging method
    7.
    发明授权
    Imaging apparatus and imaging method 有权

    公开(公告)号：US12067650B2

    公开(公告)日：2024-08-20

    申请号：US16980190

    申请日：2019-03-19

    申请人： NEC Corporation

    发明人： Chenhui Huang

    IPC分类号： G06T11/00 ,  H04N5/33 ,  H04N23/55

    CPC分类号： G06T11/003 ,  H04N23/55 ,  H04N5/33

    摘要： An imaging apparatus according to an aspect of the present disclosure includes: a filter that includes a region through which a two-dimensional signal indicating an image passes, and includes a portion which blocks at least a part of the two-dimensional signal in the region; a detector that detects a power of the two-dimensional signal passing through the filter; at least one memory storing a set of instructions; and at least one processor configured to execute the set of instructions to reconstruct the image indicated by the two-dimensional signal based on the power detected in a plurality of conditions that differ in positional relationship between the two-dimensional signal imaged on the filter and a distribution of the portion.

    Ultrasound imaging device
    8.
    发明授权
    Ultrasound imaging device 有权

    公开(公告)号：US12066532B2

    公开(公告)日：2024-08-20

    申请号：US17274387

    申请日：2019-09-11

    申请人： MODULEUS

    发明人： Adrien Bailly

    IPC分类号： G01S15/89 ,  B06B1/02 ,  G06T11/00

    CPC分类号： G01S15/8927 ,  B06B1/0215 ,  G01S15/8925 ,  G06T11/003 ,  B06B2201/76

    摘要： An ultrasonic imaging device includes a plurality of ultrasonic transducers arranged in an array of a plurality of rows and a plurality of columns, the array being divided into a plurality of sub-arrays of neighboring transducers, each including a plurality of rows and a plurality of columns, the device including, for each sub-array:



    a single transmit and/or receive circuit; and
    a combiner selector and/or splitter selector circuit configurable to couple any, alone, of the transducers of the sub-array to the transmit and/or receive circuit of the sub-array, or to simultaneously couple a plurality of the transducers of the sub-array to the transmit and/or receive circuit of the sub-array. The device further includes a control circuit adapted to individually controlling the combiner selector and/or splitter selector circuits of the different sub-arrays.