-
公开(公告)号：US20210158510A1
公开(公告)日：2021-05-27
申请号：US17014573
申请日：2020-09-08
Inventor： Qiaoying Huang , Shanhui Sun , Zhang Chen , Terrence Chen
Abstract: Described herein are neural network-based systems, methods and instrumentalities associated with estimating a thickness of an anatomical structure based on a visual representation of the anatomical structure and a machine-learned thickness prediction model. The visual representation may include an image or a segmentation mask of the anatomical structure. The thickness prediction model may be learned based on ground truth information derived by applying a partial differential equation such as Laplace's equation to the visual representation and solving the partial differential equation. When the visual representation includes an image of the anatomical structure, the systems, methods and instrumentalities described herein may also be capable of generating a segmentation mask of the anatomical structure based on the image.
-
公开(公告)号：US20210118174A1
公开(公告)日：2021-04-22
申请号：US16657125
申请日：2019-10-18
Inventor： ZIYAN WU , Shanhui Sun , Arun Innanje
Abstract: Methods and systems for guiding a patient for a medical examination using a medical apparatus. For example, a computer-implemented method for guiding a patient for a medical examination using a medical apparatus includes: receiving an examination protocol for the medical apparatus; determining a reference position based at least in part on the examination protocol; acquiring a patient position; determining a deviation metric based at least in part on comparing the patient position and the reference position; determining whether the deviation metric is greater than a pre-determined deviation threshold; and if the deviation metric is greater than a pre-determined deviation threshold: generating a positioning guidance based at least in part on the determined deviation metric, the positioning guidance including guidance for positioning the patient relative to the medical apparatus.
-
公开(公告)号：US12190508B2
公开(公告)日：2025-01-07
申请号：US17726383
申请日：2022-04-21
Inventor： Yikang Liu , Shanhui Sun , Terrence Chen , Zhang Chen , Xiao Chen
Abstract: Described herein are systems, methods, and instrumentalities associated with medical image enhancement. The medical image may include an object of interest and the techniques disclosed herein may be used to identify the object and enhance a contrast between the object and its surrounding area by adjusting at least the pixels associated with the object. The object identification may be performed using an image filter, a segmentation mask, and/or a deep neural network trained to separate the medical image into multiple layers that respectively include the object of interest and the surrounding area. Once identified, the pixels of the object may be manipulated in various ways to increase the visibility of the object. These may include, for example, adding a constant value to the pixels of the object, applying a sharpening filter to those pixels, increasing the weight of those pixels, and/or smoothing the edge areas surrounding the object of interest.
-
公开(公告)号：US12094080B2
公开(公告)日：2024-09-17
申请号：US17943724
申请日：2022-09-13
Inventor： Yikang Liu , Shanhui Sun , Terrence Chen
IPC: G06T3/4046 , G06T7/11 , G06F3/0482
CPC classification number: G06T3/4046 , G06T7/11 , G06F3/0482 , G06T2200/24 , G06T2207/20081
Abstract: A magnification system for magnifying an image based on trained neural networks is disclosed. The magnification system receives a first user input associated with a selection of a region of interest (ROI) within an input image of a site and a second user input associated with a first magnification factor of the selected ROI. The first magnification factor is associated with a magnification of the ROI in the input image. The ROI is modified based on an application of a first neural network model on the ROI. The modification of the ROI corresponds to a magnified image that is predicted in accordance with the first magnification factor. A display device is controlled to display the modified ROI.
-
公开(公告)号：US20240153089A1
公开(公告)日：2024-05-09
申请号：US17982023
申请日：2022-11-07
Inventor： Xiao Chen , Zhang Chen , Terrence Chen , Shanhui Sun
CPC classification number: G06T7/0016 , A61B5/0044 , A61B5/055 , A61B5/7267 , G06T7/30 , G06T2207/10088 , G06T2207/20081 , G06T2207/20212 , G06T2207/30048
Abstract: Real-time cardiac MRI images may be captured continuously across multiple cardiac phases and multiple slices. Machine learning-based techniques may be used to determine spatial (e.g., slices and/or views) and temporal (e.g., cardiac cycles and/or cardiac phases) properties of the cardiac images such that the images may be arranged into groups based on the spatial and temporal properties of the images and the requirements of a cardiac analysis task. Different groups of the cardiac MRI images may also be aligned with each other based on the timestamps of the images and/or by synthesizing additional images to fill in gaps.
-
Patent Agency Ranking
公开(公告)号：US11967136B2
公开(公告)日：2024-04-23
申请号：US17557984
申请日：2021-12-21
Inventor： Shanhui Sun , Yikang Liu , Xiao Chen , Zhang Chen , Terrence Chen
IPC: G06V10/774 , G06T7/00 , G06V10/82
CPC classification number: G06V10/7747 , G06T7/0012 , G06V10/82 , G06T2207/30004
Abstract: Described herein are systems, methods, and instrumentalities associated with landmark detection. The detection may be accomplished by determining a graph representation of a plurality of hypothetical landmarks detected in one or more medical images. The graph representation may include nodes that represent the hypothetical landmarks and edges that represent the relationships between paired hypothetical landmarks. The graph representation may be processed using a graph neural network such a message passing graph neural network, by which the landmark detection problem may be converted and solved as a graph node labeling problem.
-
公开(公告)号：US11941732B2
公开(公告)日：2024-03-26
申请号：US17513320
申请日：2021-10-28
Inventor： Xiao Chen , Zhang Chen , Shanhui Sun , Terrence Chen
CPC classification number: G06T11/008 , A61B5/055 , A61B5/7267 , G06T7/0012 , G06T2207/10088 , G06T2207/20081 , G06T2207/20084 , G06T2207/30016 , G06T2207/30048
Abstract: Disclosed herein are systems, methods, and instrumentalities associated with reconstructing magnetic resonance (MR) images based on multi-slice, under-sampled MRI data (e.g., k-space data). The multi-slice MRI data may be acquired using a simultaneous multi-slice (SMS) technique and MRI information associated with multiple MRI slices may be entangled in the multi-slice MRI data. A neural network may be trained and used to disentangle the MRI information and reconstruct MRI images for the different slices. A data consistency component may be used to estimate k-space data based on estimates made by the neural network, from which respective MRI images associated with multiple MRI slices may be obtained by applying a Fourier transform to the k-space data.
-
公开(公告)号：US20240061951A1
公开(公告)日：2024-02-22
申请号：US17891307
申请日：2022-08-19
Inventor： Arun Innanje , Abhishek Sharma , Benjamin Planche , Meng Zheng , Shanhui Sun , Ziyan Wu , Terrence Chen
CPC classification number: G06F21/6245 , H04L9/50 , H04L9/32 , G16H10/60 , G16H50/20 , G06F2221/2141
Abstract: A method and a system for managing healthcare records of a user are provided. The method includes storing an electronic medical record related to the user in form of a non-fungible token (NFT) written to a blockchain, associating a smart contract to the NFT in the blockchain, authorizing a request to access the electronic medical record related to the user based on the defined ownership of the electronic medical record stored in the blockchain, identifying one or more NFTs from the blockchain comprising one or more electronic medical records related to the user based on processing of the identifier information in associated one or more smart contracts therewith, in response to the request, and sending the one or more electronic medical records corresponding to the identified one or more NFTs to a requestor associated with the request.
-
公开(公告)号：US20230414132A1
公开(公告)日：2023-12-28
申请号：US17849109
申请日：2022-06-24
Inventor： Abhishek Sharma , Arun Innanje , Benjamin Planche , Meng Zheng , Shanhui Sun , Ziyan Wu , Terrence Chen
CPC classification number: A61B5/1124 , A61B5/1113 , A61B5/749 , A61B5/7267 , A61B5/4848 , G09B19/003 , A61B2505/09 , G06F3/011
Abstract: A system for providing rehabilitation in a virtual environment includes an extended reality (XR) headset to present a first rehabilitation therapy to a patient in a virtual environment. A sensing device is configured to track physical movements of the patient and a processor is configured to receive the sensing data to determine pose information. The processor is configured to determine a performance metric associated with the physical movements and compare the performance metric with a reference metric to determine whether the patient has successfully performed the defined physical movements. The processor is configured to change the first rehabilitation therapy to a second rehabilitation therapy based on a difference between the performance metric and the reference metric upon determining that the patient has unsuccessfully performed the defined physical movements. The system aids the patient by changing the rehabilitation therapies according to the performance of the patient.
-
公开(公告)号：US11734837B2
公开(公告)日：2023-08-22
申请号：US17039279
申请日：2020-09-30
Inventor： Shanhui Sun , Hanchao Yu , Xiao Chen , Terrence Chen
CPC classification number: G06T7/248 , G06N3/08 , G06T3/4046 , G06T3/4053 , G06T7/0014 , G06T2207/20016 , G06T2207/20081 , G06T2207/20084 , G06T2207/20221 , G06T2207/30048
Abstract: Described herein are neural network-based systems, methods and instrumentalities associated with estimating the motion of an anatomical structure. The motion estimation may be performed using a feature pyramid and/or a motion pyramid that correspond to multiple image scales. The motion estimation may be performed using neural networks and parameters that are learned via a training process involving a student network and a teacher network pre-pretrained with abilities to apply progressive motion compensation.
-
-
-
-
-
-
-
-
-
Search Results
110
records
(took 0.02 seconds)
