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    IMAGE DATA PROCESSING
    11.
    发明申请
    IMAGE DATA PROCESSING 有权
    图像数据处理

    公开(公告)号：US20160307360A1

    公开(公告)日：2016-10-20

    申请号：US15100994

    申请日：2014-11-28

    Applicant: Koninklijke Philips N.V.

    Inventor： Rafael WIEMKER ,  Tobias KLINDER ,  Martin BERGTHOLDT ,  Cristian LORENZ

    IPC: G06T15/08 ,  G06T7/00 ,  G06T15/06

    CPC classification number: G06T15/08 ,  A61B6/032 ,  A61B6/466 ,  A61B6/5223 ,  A61B6/5235 ,  G06T7/0002 ,  G06T7/30 ,  G06T15/06 ,  G06T2207/10081 ,  G06T2210/41

    Abstract: A method for processing image data includes obtaining a first set of 3D volumetric image data. The 3D volumetric image data includes a volume of voxels. Each voxel has an intensity. The method further includes obtaining a local voxel noise estimate for each of the voxels of the volume. The method further includes processing the volume of voxels based at least on the intensity of the voxels and the local voxel noise estimates of the voxels. An image data processor (124) includes a computer processor that at least one of: generate a 2D direct volume rendering from first 3D volumetric image data based on voxel intensity and individual local voxel noise estimates of the first 3D volumetric image data, or registers second 3D volumetric image data and first 3D volumetric image data based at least one individual local voxel noise estimates of second and first 3D volumetric image data sets.

    Abstract translation: 一种处理图像数据的方法包括获得第一组3D体积图像数据。 3D体积图像数据包括体素的体积。 每个体素都有一个强度。 该方法还包括获得体积中每个体素的局部体元噪声估计。 该方法还包括至少基于体素的强度和体素的局部体元噪声估计来处理体素的体积。 图像数据处理器（124）包括计算机处理器，其至少以下之一：基于体素强度和第一3D体积图像数据的各个局部体元噪声估计从第一3D体积图像数据生成2D直接体绘制，或者将第二3D体积图像数据寄存器 基于第二和第一3D体积图像数据集的至少一个单独局部体素噪声估计的3D体积图像数据和第一3D体积图像数据。

    IMAGE PROCESSING DEVICE AND METHOD
    13.
    发明申请
    IMAGE PROCESSING DEVICE AND METHOD 有权
    图像处理装置和方法

    公开(公告)号：US20150302602A1

    公开(公告)日：2015-10-22

    申请号：US14646044

    申请日：2013-12-02

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Rafael WIEMKER ,  Tobias KLINDER

    IPC: G06T7/00

    CPC classification number: G06T7/0083 ,  G06T7/12 ,  G06T2200/04 ,  G06T2207/10081 ,  G06T2207/20012 ,  G06T2207/20016 ,  G06T2207/20221 ,  G06T2207/30061

    Abstract: The present invention relates to an image processing device for detecting line structures in an image data set. The device comprises a model definition unit (12) for defining a line model of a line structure to be detected, said line model comprising a number of voxels, a calculation unit (14) for calculating, per voxel of interest of said image data set, several correlation values of a correlation between said line model and an image area around said voxel of interest, said image area comprising a corresponding number of voxels as said line model, wherein for each of a number of different relative orientations of said line model with respect to said image area a respective correlation value is calculated, and a determining unit (16) for determining, per voxel of interest, the maximum correlation value from said calculated correlation values and the corresponding optimal orientation at which said maximum correlation value is obtained.

    Abstract translation: 本发明涉及一种用于检测图像数据组中的线结构的图像处理装置。 该装置包括用于定义要检测的线结构的线模型的模型定义单元（12），所述线模型包括多个体素;计算单元（14），用于根据所述图像数据集的感兴趣的体素计算 所述线模型与感兴趣的所述体素周围的图像区域之间的相关性的几个相关值，所述图像区域包括相应数量的体素作为所述线模型，其中对于所述线模型的多个不同相对取向中的每一个， 对于所述图像区域计算各自的相关值，以及确定单元（16），用于根据所计算的相关值和获得所述最大相关值的对应最佳取向来确定每个感兴趣的体素的最大相关值。

    SYSTEMS AND METHODS FOR GUIDING THE ACQUISITION OF AN ULTRAOUND IMAGE
    14.
    发明申请
    SYSTEMS AND METHODS FOR GUIDING THE ACQUISITION OF AN ULTRAOUND IMAGE 有权

    公开(公告)号：US20210338203A1

    公开(公告)日：2021-11-04

    申请号：US17285379

    申请日：2019-10-14

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Laurence ROUET ,  Cybèle CIOFOLO-VEIT ,  Thierry LEFEVRE ,  Caroline Denise Francoise RAYNAUD ,  Cristian LORENZ ,  Tobias KLINDER ,  Nicole SCHADEWALDT ,  Alexander SCHMIDT-RICHBERG

    IPC: A61B8/08 ,  A61B8/00

    Abstract: The invention provides a method for guiding the acquisition of an ultrasound image. A 3D ultrasound image is acquired by an ultrasound probe at a first position and an anatomical structure is identified within the 3D ultrasound image. A target imaging plane is estimated based on the identified anatomical structure and it is determined whether the target imaging plane is present within the 3D ultrasound image. If the target imaging plane is present, a displacement between a central plane of the 3D ultrasound image and the target plane is determined. If the displacement is below a predetermined threshold, the target imaging plane is extracted and if the displacement is above the predetermined threshold, an instruction to acquire a 3D ultrasound image with the ultrasound probe at a second position, different from the first position, is generated based on the displacement. The invention further provides a method for estimating a target imaging plane. A central plane of a 3D ultrasound image is obtained, wherein the central plane contains at least part of an anatomical 40 structure and abounding box is generated around the anatomical structure. The bounding box is divided into a grid having a plurality of grid points and, for each grid point; an offset is estimated between the central plane and the target imaging plane. Finally, coordinates of the target imaging plane are estimated based on the offset for each grid point of the bounding box.

    Computer-implemented method for medical image processing
    15.
    发明申请
    Computer-implemented method for medical image processing 审中-公开

    公开(公告)号：US20200265579A1

    公开(公告)日：2020-08-20

    申请号：US16789489

    申请日：2020-02-13

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Alexander SCHMIDT-RICHBERG ,  Martin BERGTHOLDT ,  Tobias KLINDER

    IPC: G06T7/00 ,  G06T7/10 ,  G06N20/00 ,  G06K9/62

    Abstract: There is provided a computer implemented method (200) for medical image processing. The method comprises providing (202) a database of medical images and providing (204) an initial machine learning model which is trained for segmenting or classifying a medical feature in the medical images. The method also comprises extracting (206) a subset of medical images from the database based on a similarity score of the medical images and training (208) the machine learning model using the extracted subset of medical images in order to provide a refined machine learning model.

    VOLUMERTRIC IMAGE DATA VISUALIZATION
    18.
    发明申请
    VOLUMERTRIC IMAGE DATA VISUALIZATION 审中-公开
    体积图像数据可视化

    公开(公告)号：US20160260231A1

    公开(公告)日：2016-09-08

    申请号：US15028730

    申请日：2014-10-09

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Tobias KLINDER ,  Cristian LORENZ

    IPC: G06T11/00 ,  G06T15/08

    CPC classification number: G06T11/008 ,  G06T15/08 ,  G06T19/00 ,  G06T2207/10081 ,  G06T2207/30012 ,  G06T2210/41 ,  G06T2215/16 ,  G06T2219/008

    Abstract: A method includes obtaining first image data that includes voxel representing a structure of interest. The structure of interest includes a plurality of different sub-structures. The method further includes segmenting a volume of the first image data that includes only a single sub-structure for each of the plurality of different sub-structures. The method further includes creating a different local coordinate system for each of the different sub-structures for each of the volumes. The method further includes visually presenting the structure of interest through separate visual presentations of sets of reformatted images for each of the individual plurality of different sub-structures. A set of reformatted images for a sub-structure includes different cut planes generated from a corresponding segmented volume of the segmented volumes and the local coordinate system for the sub-structure.

    Abstract translation: 一种方法包括获得包括表示感兴趣结构的体素的第一图像数据。 感兴趣的结构包括多个不同的子结构。 该方法还包括分割仅包括用于多个不同子结构中的每一个的单个子结构的第一图像数据的体积。 该方法还包括为每个卷的每个不同子结构创建不同的局部坐标系。 该方法还包括通过针对每个单独的多个不同子结构的重新格式化图像的集合的单独的视觉呈现来目视地呈现感兴趣的结构。 用于子结构的一组重新格式化的图像包括从分段卷的对应分段卷和用于子结构的局部坐标系生成的不同切割平面。

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