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公开(公告)号：US11615884B2
公开(公告)日：2023-03-28
申请号：US16294576
申请日：2019-03-06
发明人： Danail Stoyanov , Petros Giataganas , Piyamate Wisanuvej , Paul Riordan , Imanol Luengo Muntion , Jean Nehme
IPC分类号： G06F3/01 , G09B9/00 , G09B23/28 , G16H40/63 , G16H50/70 , G06F16/22 , G06N5/02 , G16H10/60 , G16H30/40 , G06V20/40
摘要： A computer implemented method is provided for a virtual training system. A virtual surgical simulation associated with a type of surgical procedure is accessed. Image data associated with a controller and a workspace is received. Controller data corresponding to a controller interaction is received. A first interaction of the controller within the workspace based on at least one of the image data and the controller data is determined. Using the set of one or more transformation rules, the first interaction of the controller is transformed to a manipulation of a virtualized surgical tool in the virtual surgical simulation. A representation is output of the manipulation of the virtualized surgical tool.
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12.发明授权公开(公告)号：US11446092B2
公开(公告)日：2022-09-20
申请号：US16933454
申请日：2020-07-20
IPC分类号： A61B34/10 , G06K9/62 , G06N20/00 , G05B19/4155 , A61F5/00 , A61B17/32 , A61B17/068 , G06V20/40 , A61B17/00
摘要： The present disclosure relates to systems and methods that use computer-vision processing systems to improve patient safety during surgical procedures. Computer-vision processing systems may train machine-learning models using machine-learning techniques. The machine-learning techniques can be executed to train the machine-learning models to recognize, classify, and interpret objects within a live video feed. Certain embodiments of the present disclosure can control (or facilitate control of) surgical tools during surgical procedures using the trained machine-learning models.
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公开(公告)号：US11189379B2
公开(公告)日：2021-11-30
申请号：US16292108
申请日：2019-03-04
IPC分类号： G16H40/63 , G16H50/70 , G06F16/22 , G06K9/00 , G06N5/02 , G06F3/01 , G09B9/00 , G09B23/28 , G16H10/60 , G16H30/40
摘要： The present disclosure relates to processing data streams from a surgical procedure using multiple interconnected data structures to generate and/or continuously update an electronic output. Each surgical data structure is used to determine a current node associated with a characteristic of a surgical procedure and present relevant metadata associated with the surgical procedure. Each surgical data structure includes at least one node interconnected to one or more nodes of another data structure. The interconnected nodes between one or more data structures includes relational metadata associated with the surgical procedure.
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公开(公告)号：US20190279765A1
公开(公告)日：2019-09-12
申请号：US16292108
申请日：2019-03-04
摘要： The present disclosure relates to processing data streams from a surgical procedure using multiple interconnected data structures to generate and/or continuously update an electronic output. Each surgical data structure is used to determine a current node associated with a characteristic of a surgical procedure and present relevant metadata associated with the surgical procedure. Each surgical data structure includes at least one node interconnected to one or more nodes of another data structure. The interconnected nodes between one or more data structures includes relational metadata associated with the surgical procedure.
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公开(公告)号：US20240206989A1
公开(公告)日：2024-06-27
申请号：US18561756
申请日：2022-03-18
发明人： Imanol Luengo Muntion , Danail Stoyanov , Andre Chow , Petros Giataganas , Maria Grammatikopoulou , Maria Ruxandra Robu
CPC分类号： A61B34/20 , G06V10/26 , G06V10/82 , G06V20/46 , A61B2034/2055 , A61B2034/2065 , G06V2201/034
摘要： An aspect includes a computer-implemented method that accesses input data including spatial data and/or sensor data temporally associated with a video stream of a surgical procedure. One or more machine-learning models predict a state of the surgical procedure based on the input data. The one or more machine-learning models detect one or more surgical instruments at least partially depicted in the video stream based on the input data. A state indicator and one or more surgical instrument indicators temporally correlated with the video stream are output. A first surgical instrument of the one or more surgical instruments is identified in the video stream, and a motion profile of the first surgical instrument is determined.
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公开(公告)号：US20240169579A1
公开(公告)日：2024-05-23
申请号：US18282655
申请日：2022-03-18
发明人： Imanol Luengo Muntion , Danail V. Stoyanov , Andre Chow , Petros Giataganas , David P. Owen , Maria Grammatikopoulou , Ricardo Sanchez-Matilla , Maria Ruxandra Robu
CPC分类号： G06T7/70 , A61B34/20 , A61B90/37 , G06T7/20 , G06T7/50 , G06T11/00 , G06V20/41 , A61B2034/2065 , G06T2207/10016 , G06T2207/20081 , G06T2207/30004 , G06V2201/034
摘要： A location of an anatomical structure in image(s) from a surgical procedure is predicted using machine learning. An image/video capture device such as an endoscope, a wearable camera, a stationary camera, etc., can be used to capture the image(s). A confidence score of the prediction of the machine learning is determined. A surgeon can be provided an augmented visualization of the surgical procedure by displaying one or more graphical overlays based on the findings of the machine learning to enhance the surgeon-s information.
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公开(公告)号：US20240161497A1
公开(公告)日：2024-05-16
申请号：US18282616
申请日：2022-03-18
发明人： Imanol Luengo Muntion , Danail V. Stoyanov , Andre Chow , Petros Giataganas , David P. Owen , Maria Grammatikopoulou , Ricardo Sanchez-Matilla , Maria Ruxandra Robu
IPC分类号： G06V20/40 , G06V10/774 , G16H20/40 , G16H30/40
CPC分类号： G06V20/41 , G06V10/774 , G06V20/46 , G16H20/40 , G16H30/40 , G06V2201/034
摘要： An aspect includes a computer-implemented method that accesses input data including spatial data and/or sensor data temporally associated with a video stream of a surgical procedure. One or more machine-learning models predict a state of the surgical procedure based on the input data. The one or more machine-learning models detect one or more surgical instruments at least partially depicted in the video stream based on the input data. A state indicator and one or more surgical instrument indicators temporally correlated with the video stream are output.
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18.发明申请公开(公告)号：US20220409285A1
公开(公告)日：2022-12-29
申请号：US17899687
申请日：2022-08-31
IPC分类号： A61B34/10 , G06K9/62 , G06N20/00 , G05B19/4155 , A61F5/00 , A61B17/32 , A61B17/068 , G06V20/40
摘要： The present disclosure relates to systems and methods that use computer-vision processing systems to improve patient safety during surgical procedures. Computer-vision processing systems may train machine-learning models using machine-learning techniques. The machine-learning techniques can be executed to train the machine-learning models to recognize, classify, and interpret objects within a live video feed. Certain embodiments of the present disclosure can control (or facilitate control of) surgical tools during surgical procedures using the trained machine-learning models.
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公开(公告)号：US20220020486A1
公开(公告)日：2022-01-20
申请号：US17491658
申请日：2021-10-01
IPC分类号： G16H40/63 , G16H50/70 , G06F16/22 , G06K9/00 , G06N5/02 , G06F3/01 , G09B9/00 , G09B23/28 , G16H10/60 , G16H30/40
摘要： The present disclosure relates to processing data streams from a surgical procedure using multiple interconnected data structures to generate and/or continuously update an electronic output. Each surgical data structure is used to determine a current node associated with a characteristic of a surgical procedure and present relevant metadata associated with the surgical procedure. Each surgical data structure includes at least one node interconnected to one or more nodes of another data structure. The interconnected nodes between one or more data structures includes relational metadata associated with the surgical procedure.
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公开(公告)号：US20180357514A1
公开(公告)日：2018-12-13
申请号：US15997408
申请日：2018-06-04
发明人： Odysseas Zisimopoulos , Evangello Flouty , Imanol Luengo Muntion , Mark Stacey , Sam Muscroft , Petros Giataganas , Andre Chow , Jean Nehme , Danail Stoyanov
CPC分类号： G06K9/6256 , A61B34/10 , A61B2034/101 , A61B2034/104 , A61B2034/105 , G06K9/6262 , G06K2209/057 , G06N99/005
摘要： A set of virtual images can be generated based on one or more real images and target rendering specifications, such that the set of virtual images correspond to (for example) different rendering specifications (or combinations thereof) than do the real images. A machine-learning model can be trained using the set of virtual images. Another real image can then be processed using the trained machine-learning model. The processing can include segmenting the other real image to detect whether and/or which objects are represented (and/or a state of the object). The object data can then be used to identify (for example) a state of a procedure.
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