-
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.
-
公开(公告)号：US20230132479A1
公开(公告)日：2023-05-04
申请号：US17513392
申请日：2021-10-28
Inventor： Srikrishna Karanam , Meng Zheng , Ziyan Wu
Abstract: A three-dimensional (3D) model of a person may be obtained using a pre-trained neural network based on one or more images of the person. Such a model may be subject to estimation bias and/or other types of defects or errors. Described herein are systems, methods, and instrumentalities for refining the 3D model and/or the neural network used to generate the 3D model. The proposed techniques may extract information such as key body locations and/or a body shape from the images and refine the 3D model and/or the neural network using the extracted information. In examples, the 3D model and/or the neural network may be refined by minimizing a difference between the key body locations and/or body shape extracted from the images and corresponding key body locations and/or body shape determined from the 3D model. The refinement may be performed in an iterative and alternating manner.
-
公开(公告)号：US11461929B2
公开(公告)日：2022-10-04
申请号：US16699059
申请日：2019-11-28
Inventor： Ziyan Wu , Srikrishna Karanam
Abstract: A method for automated calibration is provided. The method may include obtaining a plurality of interest points based on prior information regarding a device and image data of the device captured by a visual sensor. The method may include identifying at least a portion of the plurality of interest points from the image data of the device. The method may also include determining a transformation relationship between a first coordinate system and a second coordinate system based on information of at least a portion of the identified interest points in the first coordinate system and in the second coordinate system that is applied to the visual sensor or the image data of the device.
-
公开(公告)号：US20250094484A1
公开(公告)日：2025-03-20
申请号：US18369766
申请日：2023-09-18
Inventor： Meng Zheng , Ziyan Wu , Benjamin Planche , Zhongpai Gao , Terrence Chen
Abstract: Described herein are machine learning (ML) based on systems, methods, and instrumentalities associated with image search and/or retrieval. An apparatus as described herein may obtain a query image and a textual description associated with the query image, and generate, using an artificial neural network (ANN), a feature representation that may represent the image and the textual description as an associated pair. Based on the feature representation, the apparatus may identify one or more images from an image repository and provide an indication regarding the one or more identified images, for example, as a ranked list.
-
公开(公告)号：US12183019B2
公开(公告)日：2024-12-31
申请号：US17994696
申请日：2022-11-28
Inventor： Srikrishna Karanam , Meng Zheng , Ziyan Wu
Abstract: A human model such as a 3D human mesh may be generated for a person in a medical environment based on one or more images of the person. The images may be captured using a sensing device that may be attached to an existing medical device such as a medical scanner in the medical environment. Such an arrangement may ensure that unblocked views of the person (e.g., body keypoints of the person) may be obtained and used to generate the human model. The position of the medical device in the medical environment may be determined and used to facilitate the human model construction such that the pose and body shape of the person in the medical environment may be accurately represented by the human model.
-
Patent Agency Ranking
公开(公告)号：US20240412452A1
公开(公告)日：2024-12-12
申请号：US18206874
申请日：2023-06-07
Inventor： Meng Zheng , Xuan Gong , Benjamin Planche , Ziyan Wu
Abstract: Disclosed herein are systems, methods and instrumentalities associated with multi-view 3D human model estimation using machine learning (ML) based techniques. These techniques may use synthetically generated data to train an ML model that may be used to progressively regress a 3D human body model based on multi-view 2D images. The training data may be synthetically generated based on statistical distributions of human poses and human body shapes, as well as a statistical distribution of camera viewpoints. The progressive regression may be performed based on consensus features shared by the multi-view images and diversity features derived from at least one of the multi-view images. Consistency between the multi-view images may also be maintained during the regression process.
-
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.
-
公开(公告)号：US12141420B2
公开(公告)日：2024-11-12
申请号：US17960367
申请日：2022-10-05
Inventor： Arun Innanje , Zheng Peng , Ziyan Wu , Qin Liu , Terrence Chen
IPC: G06T7/12 , G06F3/04842 , G06T11/00
Abstract: Click based contour editing includes detecting a selection input with respect to an image presented on a graphical user interface; designating an area of the image corresponding to the selection input as a region of interest; detecting at least one other selection input on the graphical user interface with respect to the image; determining if the at least one other selection input is within the region of interest or outside of the region of interest; and if the at least one other selection input is within the region of interest, excluding the portion of the image corresponding to the other input; or if the other selection input is outside of the region of interest, including the portion of the image corresponding to an area of the image associated with the other selection input.
-
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.
-
公开(公告)号：US20240233419A9
公开(公告)日：2024-07-11
申请号：US18128290
申请日：2023-03-30
Inventor： Meng Zheng , Wenzhe Cui , Ziyan Wu , Arun Innanje , Benjamin Planche , Terrence Chen
CPC classification number: G06V20/70 , G06V10/235
Abstract: Described herein are systems, methods, and instrumentalities associated with automatically annotating a 3D image dataset. The 3D automatic annotation may be accomplished based on a 2D manual annotation provided by an annotator and by propagating, using a set of machine-learning (ML) based techniques, the 2D manual annotation through sequences of 2D images associated with the 3D image dataset. The automatically annotated 3D image dataset may then be used to annotate other 3D image datasets upon passing a readiness assessment conducted using another set of ML based techniques. The automatic annotation of the images may be performed progressively, e.g., by processing a subset or batch of images at a time, and the ML based techniques may be trained to ensure consistency between a forward propagation and a backward propagation.
-
-
-
-
-
-
-
-
-
Search Results
101
records
(took 0.022 seconds)
