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公开(公告)号：US20250117959A1
公开(公告)日：2025-04-10
申请号：US18480665
申请日：2023-10-04
Inventor： Benjamin Planche , Ziyan Wu , Meng Zheng , Zhongpai Gao , Abhishek Sharma
IPC: G06T7/70
Abstract: Multiple predictions about the position of an object during a time period may each indicate the position of the object at a respective time during the time period. Respective validity indications corresponding to the multiple predictions may each indicate an accuracy of the corresponding prediction. Whether a change has occurred in a distribution of the predictions from a first subset of predictions to a second subset of predictions during the time period may be determined. If the change has occurred, a prediction from the first subset of predictions or the second subset of predictions may be selected, based on the validity of the predictions and/or the detection of a motion, as a best indication of the position of the object.
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公开(公告)号：US20250111517A1
公开(公告)日：2025-04-03
申请号：US18374473
申请日：2023-09-28
Inventor： Wenzhe Cui , Meng Zheng , Arun Innanje , Ziyan Wu , Terrence Chen
Abstract: An apparatus for annotating a medical image may be configured to obtain, automatically, an outline of a region of interest (ROI) in the medical image and determine, based on one or more inner control points and one or more outer control points. The one or more inner control points may be located within the ROI and the one or more outer control points may be located outside of the ROI. The outline may be subsequently adjusted based on a user input and the adjusted outline may be used to generate a segmentation of the ROI.
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公开(公告)号：US12136235B2
公开(公告)日：2024-11-05
申请号：US17559364
申请日：2021-12-22
Inventor： Meng Zheng , Srikrishna Karanam , Ziyan Wu
Abstract: Human model recovery may be realized utilizing pre-trained artificially neural networks. A first neural network may be trained to determine body keypoints of a person based on image(s) of a person. A second neural network may be trained to predict pose parameters associated with the person based on the body keypoints. A third neural network may be trained to predict shape parameters associated with the person based on depth image(s) of the person. A 3D human model may then be generated based on the pose and shape parameters respectively predicted by the second and third neural networks. The training of the second neural network may be conducted using synthetically generated body keypoints and the training of the third neural network may be conducted using normal maps. The pose and shape parameters predicted by the second and third neural networks may be further optimized through an iterative optimization process.
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公开(公告)号：US20240177420A1
公开(公告)日：2024-05-30
申请号：US17994675
申请日：2022-11-28
Inventor： Srikrishna Karanam , Runze Li , Meng Zheng , Ziyan Wu
CPC classification number: G06T17/20 , A61B34/10 , G06T7/75 , A61B2034/105 , G06T2207/30196
Abstract: A video sequence depicting a person in a medical environment may be obtained and used for determining one or more human models of the person. A first human model representing a first pose or a first body shape of the person may be determined based on a first subset of images from the video sequence, while a second human model representing a second pose or a second body shape of the person may be determined based on a second subset of images from the video sequence. The second 2D or 3D representation of the person may include an adjustment to the first 2D or 3D representation of the person based on the observation of the person provided by the second subset of images.
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公开(公告)号：US20240161440A1
公开(公告)日：2024-05-16
申请号：US17988328
申请日：2022-11-16
Inventor： Meng Zheng , Yuchun Liu , Fan Yang , Srikrishna Karanam , Ziyan Wu , Terrence Chen
CPC classification number: G06V10/24 , G06T7/80 , G06V10/751 , G06V10/82 , G06T2207/10024 , G06T2207/20081
Abstract: Images captured by different image capturing devices may have different fields of views and/or resolutions. One or more of these images may be aligned based on an image template, and additional details for the adapted images may be predicted using a machine-learned data recovery model and added to the adapted images such that the images may have the same field of view or the same resolution.
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Patent Agency Ranking
公开(公告)号：US11967102B2
公开(公告)日：2024-04-23
申请号：US17378495
申请日：2021-07-16
Inventor： Abhishek Sharma , Arun Innanje , Ziyan Wu
CPC classification number: G06T7/73 , G06N3/045 , G06T7/0012 , G06V40/103 , G06T2207/10024 , G06T2207/10028 , G06T2207/10048 , G06T2207/20081 , G06T2207/20084 , G06T2207/30196
Abstract: Image-based key points detection using a convolutional neural network (CNN) may be impacted if the key points are occluded in the image. Images obtained from additional imaging modalities such as depth and/or thermal images may be used in conjunction with RGB images to reduce or minimize the impact of the occlusion. The additional images may be used to determine adjustment values that are then applied to the weights of the CNN so that the convolution operations may be performed in a modality aware manner to increase the robustness, accuracy, and efficiency of key point detection.
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公开(公告)号：US20240108415A1
公开(公告)日：2024-04-04
申请号：US17957382
申请日：2022-09-30
Inventor： Srikrishna Karanam , Meng Zheng , Ziyan Wu
CPC classification number: A61B34/20 , A61B34/30 , A61G13/02 , G06T7/73 , G06T17/20 , G16H20/40 , A61B2034/2065 , A61G2203/34 , G06T2207/10024 , G06T2207/10028 , G06T2207/10048 , G06T2207/20081 , G06T2207/30196
Abstract: Disclosed is a method and a system for automatic positioning of a medical equipment with respect to a patient. The method includes obtaining sensor data related to the patient, from a plurality of sensors fixed relative to the medical equipment. The method further includes processing the sensor data to determine at least one pose characteristic of the patient and at least one shape characteristic of the patient. The method further includes determining at least one adjustment parameter for the medical equipment based on the at least one pose characteristic of the patient and the at least one shape characteristic of the patient. The method further includes adjusting the medical equipment based on the at least one adjustment parameter.
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公开(公告)号：US11854232B2
公开(公告)日：2023-12-26
申请号：US17651808
申请日：2022-02-20
Inventor： Ziyan Wu , Srikrishna Karanam
IPC: G06T7/73
CPC classification number: G06T7/75 , G06T7/74 , G06T2207/10024 , G06T2207/10028 , G06T2207/20081 , G06T2207/30004 , G06T2207/30196
Abstract: A system for patient positioning is provided. The system may acquire image data relating to a patient holding a posture and a plurality of patient models. Each patient model may represent a reference patient holding a reference posture, and include at least one reference interest point of the referent patient and a reference representation of the reference posture. The system may also identify at least one interest point of the patient from the image data using an interest point detection model. The system may further determine a representation of the posture of the patient based on a comparison between the at least one interest point of the patient and the at least one reference interest point in each of the plurality of patient models.
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公开(公告)号：US11836946B2
公开(公告)日：2023-12-05
申请号：US17569852
申请日：2022-01-06
Inventor： Ziyan Wu , Shanhui Sun , Arun Innanje
CPC classification number: G06T7/75 , G06T7/0012 , G06T7/136 , G16H40/67 , G16H70/00 , G06T2207/10028
Abstract: Methods and systems for guiding a patient for a medical examination using a medical apparatus. For example, a computer-implemented method for guiding a patient for a medical examination using a medical apparatus includes: receiving an examination protocol for the medical apparatus; determining a reference position based at least in part on the examination protocol; acquiring a patient position; determining a deviation metric based at least in part on comparing the patient position and the reference position; determining whether the deviation metric is greater than a pre-determined deviation threshold; and if the deviation metric is greater than a pre-determined deviation threshold: generating a positioning guidance based at least in part on the determined deviation metric, the positioning guidance including guidance for positioning the patient relative to the medical apparatus.
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公开(公告)号：US11786129B2
公开(公告)日：2023-10-17
申请号：US17666319
申请日：2022-02-07
Inventor： Srikrishna Karanam , Ziyan Wu , Georgios Georgakis
IPC: G06K9/00 , A61B5/00 , G16H30/40 , G06T7/00 , G06T7/90 , G06T17/00 , G06T7/50 , G06T7/70 , G06T17/20 , G16H10/60 , G16H30/20 , G06V20/64 , G06V40/10 , G06V40/20 , G06V20/62 , G06F18/21 , G06F18/214 , G06V10/764 , G06V10/774 , G06V10/778 , G06V10/82 , G06V10/42 , G06V10/40
CPC classification number: A61B5/0077 , A61B5/0035 , A61B5/70 , G06F18/21 , G06F18/214 , G06F18/2193 , G06T7/0012 , G06T7/50 , G06T7/70 , G06T7/90 , G06T17/00 , G06T17/20 , G06V10/40 , G06V10/42 , G06V10/764 , G06V10/774 , G06V10/7796 , G06V10/82 , G06V20/62 , G06V20/64 , G06V40/10 , G06V40/20 , G16H10/60 , G16H30/20 , G16H30/40 , G06T2200/08 , G06T2207/10024 , G06T2207/20081 , G06T2207/20084 , G06T2207/30004 , G06T2207/30196 , G06V2201/033
Abstract: Human mesh model recovery may utilize prior knowledge of the hierarchical structural correlation between different parts of a human body. Such structural correlation may be between a root kinematic chain of the human body and a head or limb kinematic chain of the human body. Shape and/or pose parameters relating to the human mesh model may be determined by first determining the parameters associated with the root kinematic chain and then using those parameters to predict the parameters associated with the head or limb kinematic chain. Such a task can be accomplished using a system comprising one or more processors and one or more storage devices storing instructions that, when executed by the one or more processors, cause the one or more processors to implement one or more neural networks trained to perform functions related to the task.
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