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公开(公告)号：US12026913B2
公开(公告)日：2024-07-02
申请号：US17564792
申请日：2021-12-29
Inventor： Ziyan Wu , Srikrishna Karanam , Meng Zheng , Abhishek Sharma
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：US20240164758A1
公开(公告)日：2024-05-23
申请号：US17989251
申请日：2022-11-17
Inventor： Ziyan Wu , Shanhui Sun , Arun Innanje , Benjamin Planche , Abhishek Sharma , Meng Zheng
CPC classification number: A61B8/5261 , A61B6/5247 , A61B8/4254 , A61B8/466 , A61B8/5223
Abstract: Sensing device(s) may be installed in a medical environment to captures images of the medical environment, which may include an ultrasound probe and a patient. The images may be processed to determine, automatically, the position of the ultrasound probe relative to the patient's body. Based on the determined position, ultrasound image(s) taken by the ultrasound probe may be aligned with a 3D patient model and displayed with the 3D patient model, for example, to track the movements of the ultrasound probe and/or provide a visual representation of the anatomical structure(s) captured in the ultrasound image(s) against the 3D patient model. The ultrasound images may also be used to reconstruct a 3D ultrasound model of the anatomical structure(s).
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公开(公告)号：US20240127929A1
公开(公告)日：2024-04-18
申请号：US17966948
申请日：2022-10-17
Inventor： Arun Innanje , Abhishek Sharma , Xiao Chen , Zhanhong Wei , Terrence Chen
IPC: G16H30/40 , G06F3/0482 , G06F3/0484 , G06F40/169 , G06V10/776 , G06V20/70
CPC classification number: G16H30/40 , G06F3/0482 , G06F3/0484 , G06F40/169 , G06V10/776 , G06V20/70 , G06V2201/03
Abstract: Disclosed is a method and a system for reviewing annotated medical images. The method includes receiving a dataset of medical images comprising one or more pre-existing annotations therein. The method also includes displaying, via a first graphical user interface, at a given instance, one of the medical images, and detecting a first input comprising a modification of at least one pre-existing annotation in the one of the medical images being displayed to define at least one modified annotation therefor and a reference for the at least one modified annotation to be associated therewith. The method also includes displaying, via a second graphical user interface, the one of the medical images having the at least one modified annotation and the associated reference for the at least one modified annotation, and detecting a second input comprising one of verification, correction, or rejection of the at least one modified annotation.
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公开(公告)号：US11734333B2
公开(公告)日：2023-08-22
申请号：US16726008
申请日：2019-12-23
Inventor： Arun Innanje , Abhishek Sharma , Terrence Chen
IPC: G06F16/36
CPC classification number: G06F16/367
Abstract: Methods and systems for organizing medical data. For example, a computer-implemented method includes receiving first data of a first data category, the first data having a first data format; extracting a first plurality of attributes from the first data using a first extractor; mapping the first plurality of attributes to an unified data format using a first mapper; receiving second data of a second data category, the second data having a second data format; extracting a second plurality of attributes from the second data using a second extractor; mapping the second plurality of attributes to the unified data format using a second mapper; and building an ontology for a use case by at least linking the first plurality of attributes and the second plurality of attributes.
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公开(公告)号：US20230148978A1
公开(公告)日：2023-05-18
申请号：US17525488
申请日：2021-11-12
Inventor： Meng Zheng , Abhishek Sharma , Srikrishna Karanam , Ziyan Wu
CPC classification number: A61B6/0407 , G06T7/70 , G06K9/6267 , G06N20/20 , G06T2207/20084
Abstract: Automated patient positioning and modelling includes a hardware processor to obtain image data from an imaging sensor, classify the image data, using a first machine learning model, as a patient pose based on one or more pre-defined protocols for patient positioning, provide a confidence score based on the classification of the image data and if the confidence score is less than a pre-determined value, re-classify the image data using a second machine learning model; or if the confidence score is greater than a pre-determined value, identify the image data as corresponding to a patient pose based on one or more pre-defined protocols for patient positioning during a scan procedure.
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Patent Agency Ranking
公开(公告)号：US20220277836A1
公开(公告)日：2022-09-01
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: G16H30/40 , G06T7/00 , G06T7/90 , G06T17/00 , G06T7/50 , G06T7/70 , G06K9/62 , G06T17/20 , G16H10/60 , G16H30/20 , A61B5/00 , G06V10/40 , G06V10/42 , G06V20/64 , G06V40/10 , G06V40/20 , G06V20/62
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：US11379727B2
公开(公告)日：2022-07-05
申请号：US16694298
申请日：2019-11-25
Inventor： Abhishek Sharma , Arun Innanje , Ziyan Wu , Shanhui Sun , Terrence Chen
Abstract: Methods and systems for enhancing a distributed medical network. For example, a computer-implemented method includes inputting training data corresponding to each local computer into their corresponding machine learning model; generating a plurality of local losses including generating a local loss for each machine learning model based at least in part on the corresponding training data; generating a plurality of local parameter gradients including generating a local parameter gradient for each machine learning model based at least in part on the corresponding local loss; generating a global parameter update based at least in part on the plurality of local parameter gradients; and updating each machine learning model hosted at each local computer of the plurality of local computers by at least updating their corresponding active parameter set based at least in part on the global parameter update.
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公开(公告)号：US11335456B2
公开(公告)日：2022-05-17
申请号：US16860901
申请日：2020-04-28
Inventor： Ziyan Wu , Srikrishna Karanam , Arun Innanje , Shanhui Sun , Abhishek Sharma , Yimo Guo , Zhang Chen
IPC: G16H30/40 , A61B5/00 , G06K9/62 , G06T7/00 , G06T7/50 , G06T7/70 , G06T17/00 , G06V10/40 , G06T7/90 , G06T17/20 , G16H10/60 , G16H30/20 , G06V10/42 , G06V20/64 , G06V40/10 , G06V40/20
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：US20220125400A1
公开(公告)日：2022-04-28
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：US20210272332A1
公开(公告)日：2021-09-02
申请号：US16804985
申请日：2020-02-28
Inventor： Arun Innanje , Shanhui Sun , Abhishek Sharma , Zhang Chen , Ziyan Wu
Abstract: A standalone image reconstruction device is configured to reconstruct the raw signals received from a radiology scanner device into a reconstructed output signal. The image reconstruction device is a vendor neutral interface between the radiology scanner device and the post processing imaging device. The reconstructed output signal is a user readable domain that can be used to generate a medical image or a three-dimensional (3D) volume. The apparatus is configured to reconstruct signals from different types of radiology scanner devices using any suitable image reconstruction protocol.
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