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    Method and system for generating a visualization plane from 3D ultrasound data
    3.
    发明授权
    Method and system for generating a visualization plane from 3D ultrasound data 有权

    公开(公告)号：US11432803B2

    公开(公告)日：2022-09-06

    申请号：US16523098

    申请日：2019-07-26

    Applicant: General Electric Company

    Inventor： Christian Fritz Perrey ,  Suvadip Mukherjee ,  Nitin Singhal ,  Rakesh Mullick

    IPC: A61B8/08 ,  G01S15/89 ,  G01S7/52 ,  A61B8/00

    Abstract: A system (e.g., an ultrasound imaging system) is provided. The system includes an ultrasound probe configured to acquire three-dimensional (3D) ultrasound data of a volumetric region of interest (ROI). The system further includes a display, a memory configured to store programmed instructions, and a controller circuit. The controller circuit includes one or more processors. The controller circuit is configured to execute the programmed instructions stored in the memory. When executing the programmed instructions, the controller circuit performs a plurality of operations. The operations includes collecting the 3D ultrasound data from an ultrasound probe and identifying a select set of the 3D ultrasound data corresponding to an object of interest within the volumetric ROI. The operations further include segmenting the object of interest from the select set of the 3D ultrasound data, generating a visualization plane of the object of interest, and displaying the visualization plane on the display.

    METHODS AND SYSTEMS FOR HIERARCHICAL MACHINE LEARNING MODELS FOR MEDICAL IMAGING
    4.
    发明申请
    METHODS AND SYSTEMS FOR HIERARCHICAL MACHINE LEARNING MODELS FOR MEDICAL IMAGING 审中-公开

    公开(公告)号：US20180240551A1

    公开(公告)日：2018-08-23

    申请号：US15900386

    申请日：2018-02-20

    Applicant: General Electric Company

    Inventor： Christian Fritz Perrey ,  Nitin Singhal

    IPC: G16H50/20 ,  G06N99/00 ,  G16H30/20

    CPC classification number: G16H50/20 ,  G06N5/003 ,  G06N20/00 ,  G16H30/20 ,  G16H30/40

    Abstract: Systems and methods are provided relating to hierarchical machine learning models to identify an anatomical structure of interest and perform diagnostic procedures for a medical diagnostic imaging system. The systems and methods organize a plurality of models into a hierarchical structure based on anatomical structures. The plurality of models are defined by a machine learning algorithm for diagnostic procedures of one or more of the anatomical structures. The systems and methods receive a medical image, identifying an anatomical structure of interest within the medical image, select at least a first model from the plurality of models based on the anatomical structure of interest, and perform a first diagnostic procedure of the anatomical structure of interest based on the first model.

    Methods and systems for hierarchical machine learning models for medical imaging
    5.
    发明授权
    Methods and systems for hierarchical machine learning models for medical imaging 有权

    公开(公告)号：US10679753B2

    公开(公告)日：2020-06-09

    申请号：US15900386

    申请日：2018-02-20

    Applicant: General Electric Company

    Inventor： Christian Fritz Perrey ,  Nitin Singhal

    IPC: G16H50/20 ,  G16H30/20 ,  G16H30/40 ,  G06N20/00 ,  G06N5/00

    Abstract: Systems and methods are provided relating to hierarchical machine learning models to identify an anatomical structure of interest and perform diagnostic procedures for a medical diagnostic imaging system. The systems and methods organize a plurality of models into a hierarchical structure based on anatomical structures. The plurality of models are defined by a machine learning algorithm for diagnostic procedures of one or more of the anatomical structures. The systems and methods receive a medical image, identifying an anatomical structure of interest within the medical image, select at least a first model from the plurality of models based on the anatomical structure of interest, and perform a first diagnostic procedure of the anatomical structure of interest based on the first model.

    SYSTEM AND METHOD FOR AUTOMATED MONITORING OF FETAL HEAD DESCENT DURING LABOR
    7.
    发明申请
    SYSTEM AND METHOD FOR AUTOMATED MONITORING OF FETAL HEAD DESCENT DURING LABOR 审中-公开
    用于在实验室中自动监测底部头部的系统和方法

    公开(公告)号：US20160045152A1

    公开(公告)日：2016-02-18

    申请号：US14457169

    申请日：2014-08-12

    Applicant: General Electric Company

    Inventor： Nitin Singhal ,  Kajoli Banerjee Krishnan ,  Christian Fritz Perrey ,  Klaus Pintoffl ,  Walter Duda, JR. ,  Francesca Patruno

    IPC: A61B5/00 ,  A61B8/08 ,  A61B5/11 ,  A61B6/03 ,  A61B5/055 ,  A61B8/13 ,  A61B5/107

    CPC classification number: A61B8/0866 ,  A61B5/055 ,  A61B5/1075 ,  A61B5/1079 ,  A61B5/1122 ,  A61B5/1128 ,  A61B5/4362 ,  A61B8/5223 ,  A61B2503/02 ,  A61B2576/00

    Abstract: A method for automatically monitoring fetal head descent in a birth canal is presented. The method includes segmenting each image in one or more images into a plurality of neighborhood components, determining a cost function corresponding to each neighborhood component in the plurality of neighborhood components in each of the one or more images, identifying at least two structures of interest in each image in the one or more images based on the cost function, wherein the at least two structures of interest include a pubic ramus and a fetal head, measuring an angle of progression based on the at least two structures of interest, and determining the fetal head descent in the birth canal based on the angle of progression.

    Abstract translation: 提出了一种自动监测胎儿胎头下降的方法。 该方法包括将一个或多个图像中的每个图像分割成多个邻域分量，确定与所述一个或多个图像中的每一个中的多个邻域分量中的每个邻域分量相对应的成本函数，识别至少两个感兴趣的结构 基于成本函数的一个或多个图像中的每个图像，其中所述至少两个感兴趣的结构包括耻骨支和胎头，基于所述至少两个感兴趣的结构来测量进展的角度，并且确定胎儿 根据进展的角度在产道中进行头部下降。

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