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公开(公告)号:US20220249014A1
公开(公告)日:2022-08-11
申请号:US17168213
申请日:2021-02-05
发明人: Bernhard Geiger , Michael Schwier , Sasa Grbic , Esther Raithel , Dana Lin , Guillaume Chabin
摘要: Systems and methods for an intuitive display of one or more anatomical objects are provided. One or more 3D medical images of one or more anatomical objects of a patient are received. Correspondences between the one or more 3D medical images and points on a 2D map representing the one or more anatomical objects are determined. The 2D map is updated with patient information extracted from the one or more 3D medical images. The updated 2D map with the determined correspondences is output.
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2.
公开(公告)号:US20240331138A1
公开(公告)日:2024-10-03
申请号:US18191108
申请日:2023-03-28
发明人: Jianing Wang , Michael Schwier , Bernhard Geiger , Sasa Grbic
CPC分类号: G06T7/0012 , A61B5/4576 , G06T7/60 , G06T7/73 , G06T2207/10088 , G06T2207/20076 , G06T2207/20081 , G06T2207/20084
摘要: Systems and methods for calculating a distance between a first point and a second point of an anatomical landmark are provided. An input medical image of an anatomical landmark of a patient is received. One or more probability maps predicting a first point and a second point of the anatomical landmark in the input medical image are generated using a machine learning based model. Locations of the first point and the second point in the input medical image are determined based on the one or more probability maps. A distance between the first point and the second point is calculated based on the locations. The locations of the first point and the second point in the input medical image and/or the calculated distance between the first point and the second point are output.
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公开(公告)号:US20220392614A1
公开(公告)日:2022-12-08
申请号:US17662475
申请日:2022-05-09
发明人: Michael Schwier , Bernhard Geiger , Sasa Grbic , Esther Raithel , Dana Lin , Guillaume Chabin
摘要: Techniques of determining a quantification of at least one characteristic of a muscle structure comprising at least one muscle and at least one tendon are disclosed. The quantification of the at least one characteristic of the rotator cuff may be determined by using at least one artificial neural network and based on one or more medical images depicting the muscle structure of a patient.
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