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    OBJECT IMAGE LABELING APPARATUS, METHOD AND PROGRAM
    2.
    发明公开
    OBJECT IMAGE LABELING APPARATUS, METHOD AND PROGRAM 审中-公开
    维多利亚计划编写的“OBJEKTBILDMARKIERUNGSVORRICHTUNG”

    公开(公告)号：EP2810250A1

    公开(公告)日：2014-12-10

    申请号：EP13713227.0

    申请日：2013-01-28

    申请人： Koninklijke Philips N.V. ,  Philips Deutschland GmbH

    发明人： VIK, Torbjørn ,  BYSTROV, Daniel ,  SCHULZ, Heinrich ,  SCHADEWALDT, Nicole ,  PETERS, Jochen

    IPC分类号： G06T7/00

    CPC分类号： G06T7/143 ,  G06K9/6206 ,  G06T7/12 ,  G06T2207/10072 ,  G06T2207/20076 ,  G06T2207/20096 ,  G06T2207/20128 ,  G06T2207/20216 ,  G06T2207/30004

    摘要： The invention relates to a labeling apparatus (1) for labeling structures of an object shown in an object image. A probability map providing unit (3) provides a probability map, the probability map indicating for different labels, which are indicative of different structures of the object, and for different positions in the probability map the probability that the respective structure, which is indicated by the respective label, is present at the respective position, wherein the probability depends on the position in the probability map. The probability map is mapped to the object image by a mapping unit (4), wherein a label assigning unit (5) assigns to a provided contour, which represents a structure in the object image, a label based on the mapped probability map. This allows automatically labeling structures of the object, which are indicated by provided contours in the object image, with relatively low computational efforts.

    摘要翻译： 本发明涉及一种用于标记物体图像中所示物体的结构的标签装置（1）。 概率图提供单元（3）提供概率图，指示不同标签的概率图，其指示对象的不同结构，以及对概率图中不同位置的概率图，其各自结构由 相应的标签存在于相应位置，其中概率取决于概率图中的位置。 通过映射单元（4）将概率图映射到对象图像，其中，标签分配单元（5）基于映射的概率图来分配表示对象图像中的结构的提供的轮廓。 这允许以相对低的计算努力自动标记在对象图像中由所提供的轮廓指示的对象的结构。

    IMAGE ACQUISITION METHOD
    4.
    发明公开
    IMAGE ACQUISITION METHOD 审中-公开

    公开(公告)号：EP4389016A1

    公开(公告)日：2024-06-26

    申请号：EP22215474.2

    申请日：2022-12-21

    申请人： Koninklijke Philips N.V.

    发明人： WEBER, Frank Michael ,  WAECHTER-STEHLE, Irina ,  GESSERT, Nils Thorben ,  PETERS, Jochen ,  LOSSAU, Tanja ,  WEHLE, Simon ,  GOOßEN, Andre ,  WILD, Sebastian ,  GROTH, Alexandra

    IPC分类号： A61B8/08

    CPC分类号： A61B8/0883 ,  A61B8/466 ,  A61B8/483 ,  A61B8/488 ,  A61B8/5207 ,  A61B8/523 ,  G01S15/8993

    摘要： A method for acquiring a set of target planar views through an anatomy of interest through processing of 3D ultrasound image data. The method processes received 3D image frames in real time to extract target planes and to process each extracted plane with a quality check algorithm. A record is kept of all target planes which have been acquired with sufficient quality, for example by removing them from a list of planes still to be captured. Optionally, each new frame need only be processed to extract planes which are yet to be acquired with sufficient quality. A user interface display is dynamically controlled so that a user is always presented with a real-time display of a planar view of at least one of the planes still to be captured with sufficient quality. The user is thus continually provided the optimal guidance imagery for controlling the acquisition apparatus to acquire new 3D frames which include image data from which the still required 2D planes can be successfully extracted with high quality.

    IMAGE SEQUENCE ANALYSIS
    7.
    发明公开
    IMAGE SEQUENCE ANALYSIS 审中-公开

    公开(公告)号：EP4044113A1

    公开(公告)日：2022-08-17

    申请号：EP21156767.2

    申请日：2021-02-12

    申请人： Koninklijke Philips N.V.

    发明人： GROTH, Alexandra ,  LOSSAU, Tanja ,  WAECHTER-STEHLE, Irina ,  WEBER, Frank Michael ,  PETERS, Jochen ,  WILD, Sebastian ,  EWALD, Dr. Arne ,  GOOßEN, André

    IPC分类号： G06T7/00 ,  G06K9/00

    摘要： A system and method for achieving more accurate results when applying an image processing task to a series of medical images of a patient, without significantly increasing processing resource. The proposed system and method is based on receiving a plurality of image sequences of a particular anatomical region, each capturing cyclical movement of an anatomical object. Each image sequence is supplied to a classifier module which employs use of one or more machine learning algorithms to derive at least one score for each image sequence indicative of predicted success or quality of a result of the image processing task if applied to the given image series. This permits an assessment to be made in advance of which of the plurality of image series is most likely to result in the best (e.g. highest quality, or greatest amount of information) results from the image processing task. This allows maximization of the quality of image processing results, without the need to actually process each of the image series with the image processing task, which would consume a large amount of processing resource and consume time.