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    Three-Dimensional Segmentation from Two-Dimensional Intracardiac Echocardiography Imaging
    3.
    发明申请
    Three-Dimensional Segmentation from Two-Dimensional Intracardiac Echocardiography Imaging 有权

    公开(公告)号：US20230113154A1

    公开(公告)日：2023-04-13

    申请号：US18059042

    申请日：2022-11-28

    申请人： Siemens Medical Solutions USA, Inc.

    发明人： Gareth Funka-Lea ,  Haofu Liao ,  Shaohua Kevin Zhou ,  Yefeng Zheng ,  Yucheng Tang

    IPC分类号： A61B8/08 ,  A61B5/06 ,  A61B5/11 ,  A61B6/12 ,  A61B8/12 ,  A61B8/13 ,  A61B8/14 ,  A61B90/00 ,  G06T15/20

    摘要： For three-dimensional segmentation from two-dimensional intracardiac echocardiography imaging, the three-dimension segmentation is output by a machine-learnt multi-task generator. Rather than the brute force approach of training the generator from 2D ICE images to output a 2D segmentation, the generator is trained from 3D information, such as a sparse ICE volume assembled from the 2D ICE images. Where sufficient ground truth data is not available, computed tomography or magnetic resonance data may be used as the ground truth for the sample sparse ICE volumes. The generator is trained to output both the 3D segmentation and a complete volume (i.e., more voxels represented than in the sparse ICE volume). The 3D segmentation may be further used to project to 2D as an input with an ICE image to another network trained to output a 2D segmentation for the ICE image. Display of the 3D segmentation and/or 2D segmentation may guide ablation of tissue in the patient.

    Three-Dimensional Segmentation from Two-Dimensional Intracardiac Echocardiography Imaging
    5.
    发明申请
    Three-Dimensional Segmentation from Two-Dimensional Intracardiac Echocardiography Imaging 审中-公开

    公开(公告)号：US20190261945A1

    公开(公告)日：2019-08-29

    申请号：US16130320

    申请日：2018-09-13

    申请人： Siemens Medical Solutions USA, Inc.

    发明人： Gareth Funka-Lea ,  Haofu Liao ,  Shaohua Kevin Zhou ,  Yefeng Zheng ,  Yucheng Tang

    IPC分类号： A61B8/08 ,  A61B8/12

    摘要： For three-dimensional segmentation from two-dimensional intracardiac echocardiography imaging, the three-dimension segmentation is output by a machine-learnt multi-task generator. Rather than the brute force approach of training the generator from 2D ICE images to output a 2D segmentation, the generator is trained from 3D information, such as a sparse ICE volume assembled from the 2D ICE images. Where sufficient ground truth data is not available, computed tomography or magnetic resonance data may be used as the ground truth for the sample sparse ICE volumes. The generator is trained to output both the 3D segmentation and a complete volume (i.e., more voxels represented than in the sparse ICE volume). The 3D segmentation may be further used to project to 2D as an input with an ICE image to another network trained to output a 2D segmentation for the ICE image. Display of the 3D segmentation and/or 2D segmentation may guide ablation of tissue in the patient.