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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：US20250029720A1
公开(公告)日：2025-01-23
申请号：US18225009
申请日：2023-07-21
Inventor： Shanhui Sun , Zhang Chen , Xiao Chen , Yikang Liu , Lin Zhao , Terrence Chen , Arun Innanje , Abhishek Sharma , Wenzhe Cui , Xiao Fan
Abstract: Disclosed herein are deep-learning based systems, methods, and instrumentalities for medical decision-making. A system as described herein may implement an artificial neural network (ANN) that may include multiple encoder neural networks and a decoder neural network. The multiple encoder neural networks may be configured to receive multiple types of patient data (e.g., text and image based patient data) and generate respective encoded representations of the patient data. The decoder neural network (e.g., a transformer decoder) may be configured to receive the encoded representations and generate a medical decision, a medical summary, or a medical questionnaire based on the encoded representations. In examples, the decoder neural network may be configured to implement a large language model (LLM) that may be pre-trained for performing the aforementioned tasks.
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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
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：US20230169657A1
公开(公告)日：2023-06-01
申请号：US17538232
申请日：2021-11-30
Inventor： Ziyan Wu , Srikrishna Karanam , Meng Zheng , Abhishek Sharma
CPC classification number: G06T7/0014 , G06T7/74 , G06T7/50 , G16H50/50 , G16H30/40 , G06N3/08 , G06T2207/10028 , G06T2207/30004 , G06T2207/20084 , G06T2207/20081
Abstract: 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
Inventor： Xiao Chen , Abhishek Sharma , Terrence Chen , Shanhui Sun
Abstract: 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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Patent Agency Ranking
公开(公告)号：US20240394870A1
公开(公告)日：2024-11-28
申请号：US18202588
申请日：2023-05-26
Inventor： Benjamin Planche , Pierre Sibut-Bourde , Ziyan Wu , Meng Zheng , Zhongpai Gao , Abhishek Sharma
Abstract: The physical characteristics of one or more anatomical structures of a person may change in accordance with conditions surrounding the determination of such physical characteristics. Machine learning based techniques may be used to determine a template representation of the one or more anatomical structures that may indicate the physical characteristics of the one or more anatomical structures free of the impact imposed by changing conditions. The template representation may then be used to predict the physical characteristics of the one or more anatomical structures under a new set of conditions, without subjecting the person to additional medical scans.
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公开(公告)号：US12138015B2
公开(公告)日：2024-11-12
申请号：US17737694
申请日：2022-05-05
Inventor： Ziyan Wu , Srikrishna Karanam , Arun Innanje , Shanhui Sun , Abhishek Sharma , Yimo Guo , Zhang Chen
IPC: G06T7/00 , A61B5/00 , G06F18/21 , G06F18/214 , G06T7/50 , G06T7/70 , G06T7/90 , G06T17/00 , G06T17/20 , G06V10/40 , G06V10/42 , G06V10/764 , G06V10/774 , G06V10/778 , G06V10/82 , G06V20/62 , G06V20/64 , G06V40/10 , G06V40/20 , G16H10/60 , G16H30/20 , G16H30/40
Abstract: A medical system may utilize a modular and extensible sensing device to derive a two-dimensional (2D) or three-dimensional (3D) human model for a patient in real-time based on images of the patient captured by a sensor such as a digital camera. The 2D or 3D human model may be visually presented on one or more devices of the medical system and used to facilitate a healthcare service provided to the patient. In examples, the 2D or 3D human model may be used to improve the speed, accuracy and consistency of patient positioning for a medical procedure. In examples, the 2D or 3D human model may be used to enable unified analysis of the patient's medical conditions by linking different scan images of the patient through the 2D or 3D human model. In examples, the 2D or 3D human model may be used to facilitate surgical navigation, patient monitoring, process automation, and/or the like.
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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
Inventor： Abhishek Sharma , Arun Innanje , Ziyan Wu , Terrence Chen
IPC: G06F15/16 , H04L61/5046 , H04L61/5038 , H04L61/5014
CPC classification number: H04L61/5046 , H04L61/5014 , H04L61/5038
Abstract: 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
Inventor： Ziyan Wu , Srikrishna Karanam , Meng Zheng , Abhishek Sharma
CPC classification number: B25J9/1676 , G06V10/768 , G06V20/64 , G06T7/215 , B25J13/08 , G05D1/0253 , A61B6/102
Abstract: 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
Inventor： Ziyan Wu , Srikrishna Karanam , Meng Zheng , Abhishek Sharma , Ren Li
Abstract: 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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