Patents by Inventor Dehan Zhu
Dehan Zhu has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20230414288Abstract: A system and method for facilitating DBS electrode trajectory planning using a machine learning (ML)-based feature identification scheme configured to identify and distinguish between various regions of interest (ROIs) and regions of avoidance (ROAs) in a patient's brain scan image. In one arrangement, standard orientation image slices as well as re-sliced images in non-standard orientations are provided in a labeled input dataset for training a CNN/ANN for distinguishing between ROIs and ROAs. Upon identification of the ROIs and ROAs in the patient's brain scan image, an optimal trajectory for implanting a DBS lead may be determined relative to a particular ROI while avoiding any ROAs.Type: ApplicationFiled: September 6, 2023Publication date: December 28, 2023Inventors: Yagna Pathak, Simeng Zhang, Dehan Zhu, Anahita Kyani, Hyun-Joo Park, Erika Ross
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Patent number: 11786309Abstract: A system and method for facilitating DBS electrode trajectory planning using a machine learning (ML)-based feature identification scheme configured to identify and distinguish between various regions of interest (ROIs) and regions of avoidance (ROAs) in a patient's brain scan image. In one arrangement, standard orientation image slices as well as re-sliced images in non-standard orientations are provided in a labeled input dataset for training a CNN/ANN for distinguishing between ROIs and ROAs. Upon identification of the ROIs and ROAs in the patient's brain scan image, an optimal trajectory for implanting a DBS lead may be determined relative to a particular ROI while avoiding any ROAs.Type: GrantFiled: December 28, 2020Date of Patent: October 17, 2023Assignee: ADVANCED NEUROMODULATION SYSTEMS, INC.Inventors: Yagna Pathak, Simeng Zhang, Dehan Zhu, Anahita Kyani, Hyun-Joo Park, Erika Ross
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Publication number: 20230240760Abstract: 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.Type: ApplicationFiled: April 5, 2023Publication date: August 3, 2023Inventors: Yagna Pathak, Hyun-Joo Park, Simeng Zhang, Anahita Kyani, Erika Ross, Dehan Zhu, Douglas Lautner
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Patent number: 11648063Abstract: 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.Type: GrantFiled: December 7, 2020Date of Patent: May 16, 2023Assignee: Advanced Neuromodulation Systems, Inc.Inventors: Yagna Pathak, Hyun-Joo Park, Simeng Zhang, Anahita Kyani, Erika Ross, Dehan Zhu, Douglas Lautner
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Publication number: 20230053982Abstract: 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.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: 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 Naivadekar, Dehan Zhu
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Publication number: 20230054906Abstract: 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.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: 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
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Publication number: 20230053914Abstract: 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.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: 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
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Publication number: 20230055984Abstract: 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.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: 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
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Publication number: 20230054788Abstract: 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.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: 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
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Publication number: 20230059718Abstract: 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.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: 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
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Publication number: 20230059282Abstract: 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.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: Yagna Pathak, Simeng Zhang, Diane Whitmer, Anahita Kyani, Hyun-Joo Park, Erika Ross, David Page, Ameya Nanivadekar, Dehan Zhu
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Publication number: 20230054261Abstract: 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.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: 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
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Publication number: 20230056291Abstract: 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.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: 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
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Publication number: 20220202491Abstract: A system and method for facilitating DBS electrode trajectory planning using a machine learning (ML)-based feature identification scheme configured to identify and distinguish between various regions of interest (ROIs) and regions of avoidance (ROAs) in a patient's brain scan image. In one arrangement, standard orientation image slices as well as re-sliced images in non-standard orientations are provided in a labeled input dataset for training a CNN/ANN for distinguishing between ROIs and ROAs. Upon identification of the ROIs and ROAs in the patient's brain scan image, an optimal trajectory for implanting a DBS lead may be determined relative to a particular ROI while avoiding any ROAs.Type: ApplicationFiled: December 28, 2020Publication date: June 30, 2022Inventors: Yagna Pathak, Simeng Zhang, Dehan Zhu, Anahita Kyani, Hyun-Joo Park, Erika Ross
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Publication number: 20220175458Abstract: 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.Type: ApplicationFiled: December 7, 2020Publication date: June 9, 2022Inventors: Yagna Pathak, Hyun-Joo Park, Simeng Zhang, Anahita Kyani, Erika Ross, Dehan Zhu, Douglas Lautner