IDENTIFYING ANATOMICAL PHRASES
    3.
    发明申请

    公开(公告)号:US20210004533A1

    公开(公告)日:2021-01-07

    申请号:US16980548

    申请日:2019-03-11

    Abstract: Methods and systems for identifying anatomical phrases in medical text. Methods and systems described herein use a syntactic approach to generate lists of relevant terms and define a grammar on these terms. Methods and systems described then search for phrases in text that conform to the grammar.

    X-ray dose distribution calculation for a computed tomography examination
    4.
    发明授权
    X-ray dose distribution calculation for a computed tomography examination 有权
    计算机断层扫描检查的X射线剂量分布计算

    公开(公告)号:US09406128B2

    公开(公告)日:2016-08-02

    申请号:US14766142

    申请日:2014-04-21

    Abstract: The invention relates to an apparatus (18) for calculating an x-ray dose distribution within an object for a computed tomography examination. A primary flux determination unit (15) determines firstly a primary flux distribution within the object, wherein then this determined primary flux distribution is used as an initial total flux distribution by a total flux determination unit (16) while applying a six-flux model algorithm. This allows the determination of the total flux distribution to start with a relatively good first approximation of the total flux distribution such that the six-flux model algorithm can determine the total flux distribution very fast. The determined total flux distribution is finally used by a dose distribution determination unit (17) for determining a total dose distribution. The apparatus allows therefore for a very fast determination of x-ray dose distributions for computed tomography examinations.

    Abstract translation: 本发明涉及一种用于计算用于计算机断层摄影检查的对象内的x射线剂量分布的装置(18)。 主要通量确定单元(15)首先确定物体内的主要通量分布,其中随后将该确定的主要通量分布用作总通量确定单元(16)的初始总通量分布,同时施加六通量模型算法 。 这允许总通量分布的确定从总通量分布的相对良好的第一近似开始,使得六通量模型算法可以非常快速地确定总通量分布。 确定的总通量分布最终由剂量分布确定单元(17)用于确定总剂量分布。 因此,该装置可以非常快速地确定计算机断层扫描检查的x射线剂量分布。

    Deep learning based scatter correction

    公开(公告)号:US11769277B2

    公开(公告)日:2023-09-26

    申请号:US16650941

    申请日:2018-09-28

    CPC classification number: G06T11/005 G06N3/08 G06T2210/41

    Abstract: An imaging system includes a computed tomography (CT) imaging device (10) (optionally a spectral CT), an electronic processor (16, 50), and a non-transitory storage medium (18, 52) storing a neural network (40) trained on simulated imaging data (74) generated by Monte Carlo simulation (60) including simulation of at least one scattering mechanism (66) to convert CT imaging data to a scatter estimate in projection space or to convert an uncorrected reconstructed CT image to a scatter estimate in image space. The storage medium further stores instructions readable and executable by the electronic processor to reconstruct CT imaging data (12, 14) acquired by the CT imaging device to generate a scatter-corrected reconstructed CT image (42). This includes generating a scatter estimate (92, 112, 132, 162, 182) by applying the neural network to the acquired CT imaging data or to an uncorrected CT image (178) reconstructed from the acquired CT imaging data.

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