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公开(公告)号：US10242292B2
公开(公告)日：2019-03-26
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
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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3.发明公开公开(公告)号：US20240156547A1
公开(公告)日：2024-05-16
申请号：US18281840
申请日：2022-03-18
IPC分类号： A61B34/00 , A61B34/10 , A61B34/20 , A61B90/00 , G06T7/00 , G06T7/50 , G06T7/70 , G06T11/00 , G06V10/26 , G06V10/774 , G06V20/40 , G06V20/50 , G16H30/40
CPC分类号： A61B34/25 , G06T7/0012 , G06T7/50 , G06T7/70 , G06T11/001 , G06V10/26 , G06V10/774 , G06V20/41 , G06V20/50 , G16H30/40 , A61B2034/107 , A61B2034/2065 , A61B2034/252 , A61B2090/364 , G06T2207/10016 , G06T2207/20081 , G06T2207/30004 , G06T2210/41 , G06V2201/031 , G06V2201/034
摘要： A surgical action to be performed during a surgical procedure is predicted using machine learning based on images and surgical instrumentation data. 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 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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4.发明授权公开(公告)号：US10758309B1
公开(公告)日：2020-09-01
申请号：US16511978
申请日：2019-07-15
IPC分类号： G05B13/02 , A61B34/10 , G06K9/62 , G06N20/00 , G05B19/4155 , A61F5/00 , A61B17/32 , A61B17/068 , G06K9/00 , 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：US20190279524A1
公开(公告)日：2019-09-12
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
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 the virtualized surgical tool in the virtual surgical simulation. A representation is output of the manipulation of the virtualized surgical tool.
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6.发明公开公开(公告)号：US20240122734A1
公开(公告)日：2024-04-18
申请号：US18394027
申请日：2023-12-22
IPC分类号： A61F5/00 , A61B1/00 , A61B17/068 , A61B17/32 , A61B34/10 , G05B19/4155 , G06F18/21 , G06N20/00 , G06V10/70 , G06V20/40
CPC分类号： A61F5/0076 , A61B1/000096 , A61B17/068 , A61B17/320016 , A61B17/320092 , A61B34/10 , G05B19/4155 , G06F18/217 , G06N20/00 , G06V10/70 , G06V20/41 , A61B2017/00212
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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8.发明申请公开(公告)号：US20210015554A1
公开(公告)日：2021-01-21
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 , G06K9/00
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：US20190164012A1
公开(公告)日：2019-05-30
申请号：US16265417
申请日：2019-02-01
发明人： Odysseas Zisimopoulos , Evangello Flouty , Imanol Luengo Muntion , Mark Stacey , Sam Muscroft , Petros Giataganas , Andre Chow , Jean Nehme , Danail Stoyanov
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. An image style can be transferred to the at least some of the virtual images of the set of virtual images to generate a stylized virtual image. A machine-learning model can be trained using a plurality of stylized 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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10.发明授权公开(公告)号：US11883312B2
公开(公告)日：2024-01-30
申请号：US17899687
申请日：2022-08-31
IPC分类号： A61F5/00 , A61B34/10 , G06N20/00 , G05B19/4155 , A61B17/32 , A61B17/068 , G06V20/40 , A61B1/00 , G06F18/21 , G06V10/70 , A61B17/00
CPC分类号： A61F5/0076 , A61B1/000096 , A61B17/068 , A61B17/320016 , A61B17/320092 , A61B34/10 , G05B19/4155 , G06F18/217 , G06N20/00 , G06V10/70 , G06V20/41 , A61B2017/00061 , A61B2017/00119 , A61B2017/00199 , A61B2017/00212 , A61B2017/320082 , A61B2017/320095 , A61B2034/107 , G05B2219/36414 , G06V2201/034
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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