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公开(公告)号：US20230343438A1
公开(公告)日：2023-10-26
申请号：US17726369
申请日：2022-04-21
Inventor： Meng Zheng , Qin Liu , Srikrishna Karanam , Ziyan Wu
IPC: G16H30/40 , G06N3/04 , G06F40/169
CPC classification number: G16H30/40 , G06N3/04 , G06F40/169
Abstract: Described herein are systems, methods, and instrumentalities associated with automatic image annotation. The annotation may be performed based on one or more manually annotated first images of an object and a machine-learned (ML) model trained to extract first features from the one or more first images. To automatically annotate a second, un-annotated image of the object, the ML model may be used to extract second features from the second image, determine information that may be indicative of the characteristics of the object in the second image based on the first and second features, and generate an annotation of the object for the second image using the determined information. The images may be obtained from various sources including, for example, sensors and/or medical scanners, and the object of interest may include anatomical structures such as organs, tumors, etc. The annotated images may be used for multiple purposes including machine learning.
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公开(公告)号：US11690579B2
公开(公告)日：2023-07-04
申请号：US16902760
申请日：2020-06-16
Inventor： Srikrishna Karanam , Ziyan Wu , Terrence Chen
IPC: A61B6/00 , A61B6/03 , G06N3/084 , G06F18/22 , G06F18/241 , G06N3/045 , G06V10/774 , G06V10/82 , G06V40/16
CPC classification number: A61B6/032 , A61B6/5211 , A61B6/54 , G06F18/22 , G06F18/241 , G06N3/045 , G06N3/084 , G06V10/774 , G06V10/82 , G06V40/171
Abstract: An apparatus is configured to receive input image data corresponding to output image data of a first radiology scanner device, translate the input image data into a format corresponding to output image data of a second radiology scanner device and generate an output image corresponding to the translated input image data on a post processing imaging device associated with the first radiology scanner device. Medical images from a new scanner can be translate to look as if they came from a scanner of another vendor.
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公开(公告)号：US20230206496A1
公开(公告)日：2023-06-29
申请号：US17564792
申请日：2021-12-29
Inventor： Ziyan Wu , Srikrishna Karanam , Meng Zheng , Abhishek Sharma
IPC: G06T7/80
CPC classification number: G06T7/80
Abstract: Automatically validating the calibration of an visual sensor network includes acquiring image data from visual sensors that have partially overlapping fields of view, extracting a representation of an environment in which the visual sensors are disposed, calculating one or more geometric relationships between the visual sensors, comparing the calculated one or more geometric relationships with previously obtained calibration information of the visual sensors, and verifying a current calibration of the visual sensors based on the comparison.
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公开(公告)号：US11676305B2
公开(公告)日：2023-06-13
申请号：US17934186
申请日：2022-09-21
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.
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公开(公告)号：US11625576B2
公开(公告)日：2023-04-11
申请号：US16685802
申请日：2019-11-15
Inventor： Ziyan Wu , Srikrishna Karanam , Arun Innanje
Abstract: A method for image processing may include: obtaining an original image of a first style, the original image being generated by a first imaging device; obtaining a target transformation model; and generating a transferred image of a second style by transferring the first style of the original image using the target transformation model. The second style may be substantially similar to a target style of one or more other images generated by a second imaging device. The second style may be different from the first style.
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Patent Agency Ranking
公开(公告)号：US11557391B2
公开(公告)日：2023-01-17
申请号：US16995446
申请日：2020-08-17
Inventor： Ziyan Wu , Srikrishna Karanam , Changjiang Cai , Georgios Georgakis
IPC: G06K9/62 , G16H30/40 , G06T7/00 , G06T7/90 , G06T17/00 , G06T7/50 , G06T7/70 , G06T17/20 , G16H10/60 , G16H30/20 , A61B5/00 , G06V10/40 , G06V10/42 , G06V20/64 , G06V40/10 , G06V40/20 , G06V20/62
Abstract: The pose and shape of a human body may be recovered based on joint location information associated with the human body. The joint location information may be derived based on an image of the human body or from an output of a human motion capture system. The recovery of the pose and shape of the human body may be performed by a computer-implemented artificial neural network (ANN) trained to perform the recovery task using training datasets that include paired joint location information and human model parameters. The training of the ANN may be conducted in accordance with multiple constraints designed to improve the accuracy of the recovery and by artificially manipulating the training data so that the ANN can learn to recover the pose and shape of the human body even with partially observed joint locations.
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公开(公告)号：US11540801B2
公开(公告)日：2023-01-03
申请号：US17081381
申请日：2020-10-27
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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公开(公告)号：US11288841B2
公开(公告)日：2022-03-29
申请号：US16656511
申请日：2019-10-17
Inventor： Ziyan Wu , Srikrishna Karanam
IPC: G06T7/73
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：US11257586B2
公开(公告)日：2022-02-22
申请号：US16863382
申请日：2020-04-30
Inventor： Srikrishna Karanam , Ziyan Wu , Georgios Georgakis
IPC: G06K9/00 , G16H30/40 , G06T7/00 , G06T7/90 , G06T17/00 , G06K9/46 , G06T7/50 , G06T7/70 , G06K9/62 , G06T17/20 , G16H10/60 , G16H30/20 , A61B5/00 , G06K9/52
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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公开(公告)号：US20210386391A1
公开(公告)日：2021-12-16
申请号：US16902760
申请日：2020-06-16
Inventor： Srikrishna Karanam , Ziyan Wu , Terrence Chen
Abstract: An apparatus is configured to receive input image data corresponding to output image data of a first radiology scanner device, translate the input image data into a format corresponding to output image data of a second radiology scanner device and generate an output image corresponding to the translated input image data on a post processing imaging device associated with the first radiology scanner device. Medical images from a new scanner can be translate to look as if they came from a scanner of another vendor.
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