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    ANATOMY-AWARE CONTOUR EDITING METHOD AND SYSTEM FOR IMPLEMENTING SAID METHOD
    71.
    发明公开
    ANATOMY-AWARE CONTOUR EDITING METHOD AND SYSTEM FOR IMPLEMENTING SAID METHOD 审中-公开

    公开(公告)号：US20240104721A1

    公开(公告)日：2024-03-28

    申请号：US17953484

    申请日：2022-09-27

    Applicant: Shanghai United Imaging Intelligence Co., LTD.

    Inventor： Arun Innanje ,  Xiao Chen ,  Shanhui Sun ,  Zhanhong Wei ,  Terrence Chen

    IPC: G06T7/00

    CPC classification number: G06T7/0012 ,  G06T2207/10088 ,  G06T2207/30048

    Abstract: An anatomy-aware contouring editing method includes receiving an image, wherein the image represents an anatomically recognizable structure; identifying a first image segment representing part of the anatomically recognizable structure; annotating the first image segment to generate a label of the part; drawing a contour along a boundary of the part; receiving a first input from a user device indicative of a region of contour failure, wherein the region of contour failure includes a portion of a contour that requires editing; editing the contour for generating an edited contour based on the first input and anatomical information; and updating another contour of another part of the anatomically recognizable structure based on the edited contour, wherein the another part is anatomically related to the part.

    MULTI-CONTRAST MRI SAMPLING AND IMAGE RECONSTRUCTION
    73.
    发明公开
    MULTI-CONTRAST MRI SAMPLING AND IMAGE RECONSTRUCTION 审中-公开

    公开(公告)号：US20230366964A1

    公开(公告)日：2023-11-16

    申请号：US17741307

    申请日：2022-05-10

    Applicant: Shanghai United Imaging Intelligence Co., Ltd.

    Inventor： Xiao Chen ,  Zhang Chen ,  Yikang Liu ,  Shanhui Sun ,  Terrence Chen ,  Lin Zhao

    IPC: G01R33/56 ,  G01R33/561

    CPC classification number: G01R33/5608 ,  G01R33/5611 ,  G06N3/0454

    Abstract: Described herein are systems, methods, and instrumentalities associated with reconstruction of multi-contrast magnetic resonance imaging (MRI) images. The reconstruction may be performed based on under-sampled MRI data collected for the multiple contrasts using corresponding sampling patterns. The sampling patterns and the reconstruction operations for the multiple contrasts may be jointly optimized using deep learning techniques implemented through one or more neural networks. An end-to-end reconstruction optimizing framework is provided with which information collected while processing one contrast may be stored and used for another contrast. A differentiable sampler is described for obtaining the under-sampled MRI data from a k-space and a novel holistic recurrent neural network is used to reconstruct MRI images based on the under-sampled MRI data.

    SYSTEMS AND METHODS FOR ENHANCING MEDICAL IMAGES
    74.
    发明公开
    SYSTEMS AND METHODS FOR ENHANCING MEDICAL IMAGES 审中-公开

    公开(公告)号：US20230342916A1

    公开(公告)日：2023-10-26

    申请号：US17726383

    申请日：2022-04-21

    Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.

    Inventor： Yikang Liu ,  Shanhui Sun ,  Terrence Chen ,  Zhang Chen ,  Xiao Chen

    IPC: G06T5/00 ,  G06T7/00 ,  G06T7/10

    CPC classification number: G06T7/0012 ,  G06T5/007 ,  G06T7/10 ,  G06T2207/10116 ,  G06T2207/20084

    Abstract: Described herein are systems, methods, and instrumentalities associated with medical image enhancement. The medical image may include an object of interest and the techniques disclosed herein may be used to identify the object and enhance a contrast between the object and its surrounding area by adjusting at least the pixels associated with the object. The object identification may be performed using an image filter, a segmentation mask, and/or a deep neural network trained to separate the medical image into multiple layers that respectively include the object of interest and the surrounding area. Once identified, the pixels of the object may be manipulated in various ways to increase the visibility of the object. These may include, for example, adding a constant value to the pixels of the object, applying a sharpening filter to those pixels, increasing the weight of those pixels, and/or smoothing the edge areas surrounding the object of interest.

    Systems and methods for machine learning based modeling
    80.
    发明授权
    Systems and methods for machine learning based modeling 有权

    公开(公告)号：US11604984B2

    公开(公告)日：2023-03-14

    申请号：US16686539

    申请日：2019-11-18

    Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.

    Inventor： Abhishek Sharma ,  Arun Innanje ,  Ziyan Wu ,  Shanhui Sun ,  Terrence Chen

    IPC: G06N3/08 ,  G06N3/04

    Abstract: A system comprising a first computing apparatus in communication with multiple second computing apparatuses. The first computing apparatus may obtain a plurality of first trained machine learning models for a task from the multiple second computing apparatuses. At least a portion of parameter values of the plurality of first trained machine learning models may be different from each other. The first computing apparatus may also obtain a plurality of training samples. The first computing apparatus may further determine, based on the plurality of training samples, a second trained machine learning model by learning from the plurality of first trained machine learning models.

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