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    METHOD AND APPARATUS FOR COMPENSATING IMAGE SEGMENTATION LINES
    2.
    发明公开
    METHOD AND APPARATUS FOR COMPENSATING IMAGE SEGMENTATION LINES 审中-公开

    公开(公告)号：EP4148666A1

    公开(公告)日：2023-03-15

    申请号：EP21208678.9

    申请日：2021-11-17

    Applicant: Acer Medical Inc.

    Inventor： HUANG, Shih-Ho ,  YIN, Ming-Tzuo

    IPC: G06T7/10 ,  G06V10/44 ,  G06T7/12 ,  G06T7/181

    Abstract: A method and an apparatus for compensating image segmentation lines (20) are provided. In the method, image segmentation is applied to a medical image (42) captured by using a segmentation model (44) to obtain a segmentation image (46) including at least one segmentation line (12a) between multiple layers in the medical image. Convolution computation is then performed on the segmentation image (46) by using a kernel (60, 60a) of a trained classification model (50) to predict a location of a next pixel connected to a current pixel in the respective segmentation line (12a) within the segmentation image (46), in which the pixel to be predicted is limited to a neighboring pixel of the current pixel in a prediction direction. The predicted pixels are connected to form a compensated segmentation line (14a) for each segmentation line (12a).

    Method for segmentation of dental images
    6.
    发明授权
    Method for segmentation of dental images 有权

    公开(公告)号：EP2734147B1

    公开(公告)日：2018-08-29

    申请号：EP12814726.1

    申请日：2012-07-19

    Applicant: Carestream Dental Technology Topco Limited

    Inventor： CHEN, Shoupu ,  RAY, Lawrence, A. ,  INGLESE, Jean-Marc

    IPC: G06T7/12 ,  G06T7/181 ,  G06T7/194 ,  A61B6/14

    CPC classification number: G06T7/12 ,  A61B6/14 ,  G06T7/181 ,  G06T7/194 ,  G06T2207/10081 ,  G06T2207/30036

    Abstract: A method for segmenting a feature of interest from a volume image acquires image data elements from the image of a subject. At least one view of the acquired volume is displayed. One or more boundary points along a boundary of the feature of interest are identified according to one or more geometric primitives defined by a user with reference to the displayed view. A foreground seed curve defined according to the one or more identified boundary points and a background seed curve encompassing and spaced apart from the foreground seed curve are formed. Segmentation is applied to the volume image according to foreground values that are spatially bounded within the foreground seed curve and according to background values that lie outside the background seed curve. An image of the segmented feature of interest is displayed.

    IMAGE PROCESSING DEVICE FOR MEDICAL USE AND IMAGE PROCESSING METHOD FOR MEDICAL USE
    7.
    发明公开
    IMAGE PROCESSING DEVICE FOR MEDICAL USE AND IMAGE PROCESSING METHOD FOR MEDICAL USE 审中-公开
    BILDBEARBEITUNGSVORRICHTUNG ZUR MEDIZINISCHEN VERWENDUNG UND BILDBEARBEITUNGSVERFAHREN ZUR MEDIZINISCHEN VERWENDUNG

    公开(公告)号：EP2057932A4

    公开(公告)日：2017-08-02

    申请号：EP07744947

    申请日：2007-06-08

    Applicant: OLYMPUS CORP

    Inventor： SAWA MIHO ,  NISHIMURA HIROKAZU ,  TANAKA HIDEKI ,  INOUE RYOKO ,  NAKAMURA KENJI

    IPC: A61B1/04 ,  G06T1/00 ,  G06T7/00 ,  G06T7/13 ,  G06T7/181 ,  G06T7/44 ,  G06T7/507

    CPC classification number: G06T7/0012 ,  A61B1/042 ,  G06T7/13 ,  G06T7/181 ,  G06T7/44 ,  G06T7/507 ,  G06T2200/04 ,  G06T2207/10016 ,  G06T2207/10068 ,  G06T2207/20021 ,  G06T2207/20132 ,  G06T2207/30032

    Abstract: A medical image processing apparatus of the present invention includes: a three-dimensional model estimating section for estimating a three-dimensional model of an object based on a two-dimensional image of an image of the object which is inputted from a medical image pickup apparatus; an image dividing section for dividing the two-dimensional image into a plurality of regions each of which includes at least one or more pixels; a feature value calculation section for calculating a feature value according to a grayscale of each pixel in one region for each of the plurality of regions; and a lesion detection reference setting section for setting lesion detection reference for detecting a locally protruding lesion in the regions of the three-dimensional model which correspond to each of the plurality of regions, based on the feature value according to the grayscale.

    Abstract translation: 本发明的医用图像处理装置的特征在于，具备：三维模型推定部，其基于从医用图像摄像装置输入的被检体的图像的二维图像，推定被检体的三维模型 ; 图像分割部分，用于将二维图像分割成多个区域，每个区域包括至少一个或多个像素; 特征值计算部分，用于针对所述多个区域中的每一个计算根据一个区域中的每个像素的灰度的特征值; 以及病变检测基准设置部分，用于基于根据灰度的特征值来设置用于检测在与多个区域中的每个区域相对应的三维模型的区域中的局部突出病变的病变检测参考。

    TAB FOLDING DETECTION METHOD AND APPARATUS, ELECTRONIC DEVICE, AND STORAGE MEDIUM
    8.
    发明公开
    TAB FOLDING DETECTION METHOD AND APPARATUS, ELECTRONIC DEVICE, AND STORAGE MEDIUM 有权 转让

    公开(公告)号：EP4354392A1

    公开(公告)日：2024-04-17

    申请号：EP22873961.1

    申请日：2022-08-29

    Applicant: Contemporary Amperex Technology Co., Limited

    Inventor： HUANG, Qiangwei ,  JIANG, Guannan ,  WANG, Zhiyu

    IPC: G06T7/00 ,  G06T7/12 ,  G06T7/181 ,  G01N21/88

    CPC classification number: G06T7/0006 ,  G06T7/12 ,  G06T7/181 ,  G06T2207/3010820130101 ,  G06T2207/2004420130101

    Abstract: This application provides a tab bending detection method and apparatus, an electronic device, and a storage medium. The method includes: performing skeleton extraction on a sectional image of multiple layers of tabs to obtain a skeleton image of the multiple layers of tabs; merging damaged connected components in the skeleton image to obtain a merged connected component, where the damaged connected components are connected components on which breaking occurs in a same tab section; calculating a target number of the multiple layers of tabs based on the merged connected component and an undamaged connected component; and detecting, based on the target number and a preset number, whether any tab in the multiple layers of tabs is in a bending state. The damaged connected components are merged to obtain the merged connected component. The target number of the multiple layers of tabs calculated based on the merged connected component and the undamaged connected component is more accurate, thus making the tab bending detection more accurate.

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