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公开(公告)号：US11967102B2
公开(公告)日：2024-04-23
申请号：US17378495
申请日：2021-07-16
发明人： Abhishek Sharma , Arun Innanje , Ziyan Wu
CPC分类号： G06T7/73 , G06N3/045 , G06T7/0012 , G06V40/103 , G06T2207/10024 , G06T2207/10028 , G06T2207/10048 , G06T2207/20081 , G06T2207/20084 , G06T2207/30196
摘要： 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：US20230169657A1
公开(公告)日：2023-06-01
申请号：US17538232
申请日：2021-11-30
发明人： Ziyan Wu , Srikrishna Karanam , Meng Zheng , Abhishek Sharma
CPC分类号： G06T7/0014 , G06T7/74 , G06T7/50 , G16H50/50 , G16H30/40 , G06N3/08 , G06T2207/10028 , G06T2207/30004 , G06T2207/20084 , G06T2207/20081
摘要： The shape and/or location of an organ may change in accordance with changes in the body shape and/or pose of a patient. Described herein are systems, methods, and instrumentalities for automatically determining, using an artificial neural network (ANN), the shape and/or location of the organ based on human models that reflect the body shape and/or pose the patient. The ANN may be trained to learn the spatial relationship between the organ and the body shape or pose of the patient. Then, at an inference time, the ANN may be used to determine the relationship based on a first patient model and a first representation (e.g., a point cloud) of the organ so that given a second patient model thereafter, the ANN may automatically determine the shape and/or location of the organ corresponding to the body shape or pose of the patient indicated by the second patient model.
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公开(公告)号：US20220338816A1
公开(公告)日：2022-10-27
申请号：US17236173
申请日：2021-04-21
发明人： Xiao Chen , Abhishek Sharma , Terrence Chen , Shanhui Sun
摘要： A system and method for cardiac function and myocardial strain analysis include techniques and structure for classifying a set of cardiac images according to their views, detecting a heart range and valid short-axis slices in the set of cardiac images, determining heart segment locations, segmenting heart anatomies for each time frame and each slice, calculating volume related parameters, determining key physiological time points, calculating myocardium transmural thickness and deriving a cardiac function measure from the myocardium transmural thickness at the key physiological time points, estimating a dense motion field from the key physiological time points as applied to the set of cardiac images, calculating myocardial strain along different myocardium directions from the dense motion field, and providing the cardiac function measure and myocardial strain calculation to a user through a user interface.
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公开(公告)号：US11811729B1
公开(公告)日：2023-11-07
申请号：US17889480
申请日：2022-08-17
发明人： Abhishek Sharma , Arun Innanje , Ziyan Wu , Terrence Chen
IPC分类号： G06F15/16 , H04L61/5046 , H04L61/5038 , H04L61/5014
CPC分类号： H04L61/5046 , H04L61/5014 , H04L61/5038
摘要： Disclosed is a system and a method for configuring an IP device to be discoverable to a client device over a local network having a DHCP server for assigning dynamic IP addresses. The method includes obtaining a dynamic IP address assigned to the IP device upon completion of boot process for the IP device; checking if a static IP address has been set for the IP device; determining if the dynamic IP address and the static IP address are in a same subnet of the local network; implementing the static IP address set for the IP device, if the dynamic IP address and the static IP address are in the same subnet of the local network; and implementing the dynamic IP address assigned to the IP device, if the dynamic IP address and the static IP address are not in the same subnet of the local network.
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公开(公告)号：US20230202044A1
公开(公告)日：2023-06-29
申请号：US17564919
申请日：2021-12-29
发明人： Ziyan Wu , Srikrishna Karanam , Meng Zheng , Abhishek Sharma
CPC分类号： B25J9/1676 , G06V10/768 , G06V20/64 , G06T7/215 , B25J13/08 , G05D1/0253 , A61B6/102
摘要： An apparatus for automated collision avoidance includes a sensor configured to detect an object of interest, predicting a representation of the object of interest at a future point in time, calculating an indication of a possibility of a collision with the object of interest based on the representation of the object of interest at the future point in time, and executing a collision avoidance action based on the indication.
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公开(公告)号：US20230132936A1
公开(公告)日：2023-05-04
申请号：US18149111
申请日：2023-01-01
发明人： Ziyan Wu , Srikrishna Karanam , Meng Zheng , Abhishek Sharma , Ren Li
摘要： Systems, methods and instrumentalities are described herein for automating a medical environment. The automation may be realized using one or more sensing devices and at least one processing device. The sensing devices may be configured to capture images of the medical environment and provide the images to the processing device. The processing device may determine characteristics of the medical environment based on the images and automate one or more aspects of the operations in the medical environment. These characteristics may include, e.g., people and/or objects present in the images and respective locations of the people and/or objects in the medical environment. The operations that may be automated may include, e.g., maneuvering and/or positioning a medical device based on the location of a patient, determining and/or adjusting the parameters of a medical device, managing a workflow, providing instructions and/or alerts to a patient or a physician, etc.
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公开(公告)号：US20240341903A1
公开(公告)日：2024-10-17
申请号：US18134234
申请日：2023-04-13
发明人： Abhishek Sharma , Arun Innanje , Terrence Chen
CPC分类号： A61B90/36 , A61B34/10 , A61B2034/105 , A61B2090/365
摘要： An object or person in a medical environment may be identified based on images of the medical environment. The identification may include determining an identifier associated with the object or the person, a position of the object or the person in the medical environment, and a three-dimensional (3D) shape/pose of the object or the person. Representation information that indicates at least the determined identifier, position in the medical environment, and 3D shape/pose of the object or the person may be generated and then used (e.g., by a visualization device) together with one or more predetermined 3D models to determine a 3D model for the object or the person identified in the medical environment and generate a visual depiction of at least the object or the person in the medical environment based on the determined 3D model and the position of the object or the person in the medical environment.
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公开(公告)号：US20240331446A1
公开(公告)日：2024-10-03
申请号：US18126853
申请日：2023-03-27
发明人： Zhongpai Gao , Abhishek Sharma , Meng Zheng , Benjamin Planche , Ziyan Wu , Terrence Chen
CPC分类号： G06V40/20 , G06V10/26 , G06V10/40 , G06V10/82 , G06V40/11 , G06V10/774 , G06V2201/03
摘要： Automatic hand gesture determination may be a challenging task considering the complex anatomy and high dimensionality of the human hand. Disclosed herein are systems, methods, and instrumentalities associated with recognizing a hand gesture in spite of the challenges. An apparatus in accordance with embodiments of the present disclosure may use machine learning based techniques to identify the area of an image that may contain a hand and to determine an orientation of the hand relative to a pre-defined direction. The apparatus may then adjust the area of the image containing the hand to align the orientation of the hand with the pre-defined direction and/or to scale the image area to a pre-defined size. Based on the adjusted image area, the apparatus may detect a plurality of hand landmarks and predict a gesture indicated by the hand based on the plurality of detected landmarks.
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公开(公告)号：US12051204B2
公开(公告)日：2024-07-30
申请号：US17538232
申请日：2021-11-30
发明人： Ziyan Wu , Srikrishna Karanam , Meng Zheng , Abhishek Sharma
CPC分类号： G06T7/0014 , G06N3/08 , G06T7/50 , G06T7/74 , G16H30/40 , G16H50/50 , G06T2207/10028 , G06T2207/20081 , G06T2207/20084 , G06T2207/30004
摘要： The shape and/or location of an organ may change in accordance with changes in the body shape and/or pose of a patient. Described herein are systems, methods, and instrumentalities for automatically determining, using an artificial neural network (ANN), the shape and/or location of the organ based on human models that reflect the body shape and/or pose the patient. The ANN may be trained to learn the spatial relationship between the organ and the body shape or pose of the patient. Then, at an inference time, the ANN may be used to determine the relationship based on a first patient model and a first representation (e.g., a point cloud) of the organ so that given a second patient model thereafter, the ANN may automatically determine the shape and/or location of the organ corresponding to the body shape or pose of the patient indicated by the second patient model.
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公开(公告)号：US12045695B2
公开(公告)日：2024-07-23
申请号：US16804907
申请日：2020-02-28
发明人： Srikrishna Karanam , Ziyan Wu , Abhishek Sharma , Arun Innanje , Terrence Chen
摘要： Data samples are transmitted from a central server to at least one local server apparatus. The central server receives a set of predictions from the at least one local server apparatus that are based on the transmitted set of data samples. The central server trains a central model based on the received set of predictions. The central model, or a portion of the central model corresponding to a task of interest, can then be sent to the at least one local server apparatus. Neither local data from local sites nor trained models from the local sites are transmitted to the central server. This ensures protection and security of data at the local sites.
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