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Patent Agency Ranking
11.发明授权公开(公告)号：US11648063B2
公开(公告)日：2023-05-16
申请号：US17113385
申请日：2020-12-07
Applicant: Advanced Neuromodulation Systems, Inc.
Inventor： Yagna Pathak , Hyun-Joo Park , Simeng Zhang , Anahita Kyani , Erika Ross , Dehan Zhu , Douglas Lautner
IPC: A61B8/00 , A61B34/20 , G06K9/62 , G06T7/73 , A61N1/05 , G16H30/40 , G16H20/40 , G16H50/20 , G06V10/40 , A61B90/00
CPC classification number: A61B34/20 , A61N1/0534 , G06K9/6257 , G06T7/73 , G06V10/40 , G16H20/40 , G16H30/40 , G16H50/20 , A61B2034/2065 , A61B2090/374 , A61B2090/3762 , G06T2207/10064 , G06T2207/10081 , G06T2207/10088 , G06T2207/20021 , G06T2207/20081 , G06T2207/20084 , G06T2207/30016 , G06V2201/031
Abstract: The present disclosure provides systems and methods for estimating an orientation of an implanted deep brain stimulation (DBS) lead. Such methods include generating an initial image dataset, down-sampling a respective image or adding noise to images of the subset of the initial image dataset, and re-slicing at least a subset of the modified image dataset along an alternative primary imaging axis, to generate an integrated image dataset. The method also include partitioning the integrated image dataset into a preliminary training image dataset and a testing image dataset, and re-sizing at least a subset of the preliminary training image dataset with a localized field of view around a depicted DBS lead, to generate a training image dataset. The method further includes training a machine-learning model using the training image dataset, and executing the trained machine-learning model to estimate, during a DBS implantation procedure, an orientation of a subject implanted DBS lead.
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公开(公告)号：US20230056291A1
公开(公告)日：2023-02-23
申请号：US17891098
申请日：2022-08-18
Applicant: Advanced Neuromodulation Systems, Inc.
Inventor： Mary Khun Hor-Lao , Binesh Balasingh , Scott DeBates , Douglas Alfred Lautner , Yagna Pathak , Simeng Zhang , Diane Whitmer , Anahita Kyani , Hyun-Joo Park , Erika Ross , David Page , Ameya Nanivadekar , Dehan Zhu
Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.
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公开(公告)号：US20230055984A1
公开(公告)日：2023-02-23
申请号：US17891096
申请日：2022-08-18
Applicant: Advanced Neuromodulation Systems, Inc.
Inventor： Mary Khun Hor-Lao , Binesh Balasingh , Scott DeBates , Douglas Alfred Lautner , Yagna Pathak , Simeng Zhang , Diane Whitmer , Anahita Kyani , Hyun-Joo Park , Erika Ross , David Page , Ameya Nanivadekar , Dehan Zhu
Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.
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公开(公告)号：US20230054261A1
公开(公告)日：2023-02-23
申请号：US17891102
申请日：2022-08-18
Applicant: Advanced Neuromodulation Systems, Inc.
Inventor： Mary Khun Hor-Lao , Binesh Balasingh , Scott DeBates , Douglas Alfred Lautner , Yagna Pathak , Simeng Zhang , Diane Whitmer , Anahita Kyani , Hyun-Joo Park , Erika Ross , David Page , Ameya Nanivadekar , Dehan Zhu
Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.
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公开(公告)号：US20230053914A1
公开(公告)日：2023-02-23
申请号：US17891074
申请日：2022-08-18
Applicant: Advanced Neuromodulation Systems, Inc.
Inventor： Mary Khun Hor-Lao , Binesh Balasingh , Scott DeBates , Douglas Alfred Lautner , Yagna Pathak , Simeng Zhang , Diane Whitmer , Anahita Kyani , Hyun-Joo Park , Erika Ross , David Page , Ameya Nanivadekar , Dehan Zhu
Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.
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