-
公开(公告)号：US11836946B2
公开(公告)日：2023-12-05
申请号：US17569852
申请日：2022-01-06
Inventor： Ziyan Wu , Shanhui Sun , Arun Innanje
CPC classification number: G06T7/75 , G06T7/0012 , G06T7/136 , G16H40/67 , G16H70/00 , G06T2207/10028
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：US20230367850A1
公开(公告)日：2023-11-16
申请号：US17741323
申请日：2022-05-10
Inventor： Xiao Chen , Yikang Liu , Zhang Chen , Shanhui Sun , Terrence Chen , Daniel Hyungseok Pak
CPC classification number: G06K9/6256 , A61B5/7267 , G01R33/5608 , G06N20/00 , G06T11/005
Abstract: Described herein are systems, methods, and instrumentalities associated with processing complex-valued MRI data using a machine learning (ML) model. The ML model may be learned based on synthetically generated MRI training data and by applying one or more meta-learning techniques. The MRI training data may be generated by adding phase information to real-valued MRI data and/or by converting single-coil MRI data into multi-coil MRI data based on coil sensitivity maps. The meta-learning process may include using portions of the training data to conduct a first round of learning to determine updated model parameters and using remaining portions of the training data to test the updated model parameters. Losses associated with the testing may then be determined and used to refine the model parameters. The ML model learned using these techniques may be adopted for a variety of tasks including, for example, MRI image reconstruction and/or de-noising.
-
公开(公告)号：US11803939B2
公开(公告)日：2023-10-31
申请号：US17242473
申请日：2021-04-28
Inventor： Yikang Liu , Zhang Chen , Xiao Chen , Shanhui Sun , Terrence Chen
CPC classification number: G06T3/4053 , G06N3/088 , G06T3/4046 , G06T11/006 , G16H30/40
Abstract: An unsupervised machine learning method with self-supervision losses improves a slice-wise spatial resolution of 3D medical images with thick slices, and does not require high resolution images as the ground truth for training. The method utilizes information from high-resolution dimensions to increase a resolution of another desired dimension.
-
公开(公告)号：US11763134B2
公开(公告)日：2023-09-19
申请号：US16749964
申请日：2020-01-22
Inventor： Zhang Chen , Shanhui Sun , Terrence Chen
IPC: G06N3/045 , G06N3/08 , G01R33/56 , G01R33/561
CPC classification number: G06N3/045 , G01R33/5608 , G01R33/5611 , G06N3/08 , G06T2207/20081 , G06T2207/20084
Abstract: A system for image reconstruction in magnetic resonance imaging (MRI) is provided. The system may obtain undersampled k-space data associated with an object, wherein the undersampled K-space data may be generated based on magnetic resonance (MR) signals collected by an MR scanner that scans the object. The system may construct an ordinary differential equation (ODE) that formulates a reconstruction of an MR image based on the undersampled k-space data. The system may further generate the MR image of the object by solving the ODE based on the undersampled k-space data using an ODE solver.
-
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.
-
Patent Agency Ranking
公开(公告)号：US11348230B2
公开(公告)日：2022-05-31
申请号：US16664710
申请日：2019-10-25
Inventor： Shanhui Sun , Zhang Chen , Terrence Chen
Abstract: Systems and methods for generating and tracking shapes of a target may be provided. The method may include obtaining at least one first resolution image corresponding to at least one of a sequence of time frames of a medical scan. The method may include determining, according to a predictive model, one or more shape parameters regarding a shape of a target from the at least one first resolution image. The method may include determining, based on the one or more shape parameters and a shape model, at least one shape of the target from the at least one first resolution image. The method may further include generating a second resolution visual representation of the target by rendering the determined shape of the target.
-
公开(公告)号：US11334995B2
公开(公告)日：2022-05-17
申请号：US17014594
申请日：2020-09-08
Inventor： Yimo Guo , Shanhui Sun , Terrence Chen
IPC: G06T7/00 , G06T7/11 , G06K9/62 , G06N3/04 , G16H50/50 , G16H50/30 , G16H30/40 , G06F3/0485 , G06T11/20 , G06T13/80 , G06T19/00 , G06T7/55 , G06T7/73 , G06T7/246 , A61B5/00 , A61B5/11 , G06T3/00 , G06N3/08
Abstract: Described herein are systems, methods and instrumentalities associated with image segmentation. The systems, methods and instrumentalities have a hierarchical structure for producing a coarse segmentation of an anatomical structure and then refining the coarse segmentation based on a shape prior of the anatomical structure. The coarse segmentation may be generated using a multi-task neural network and based on both a segmentation loss and a regression loss. The refined segmentation may be obtained by deforming the shape prior using one or more of a shape-based model or a learning-based model.
-
公开(公告)号：US11315246B2
公开(公告)日：2022-04-26
申请号：US17014609
申请日：2020-09-08
Inventor： Arun Innanje , Xiao Chen , Shanhui Sun , Terrence Chen
IPC: G06T7/12 , G06T7/00 , G06T7/11 , G06K9/62 , G06N3/04 , G16H50/50 , G16H50/30 , G16H30/40 , G06F3/0485 , G06T11/20 , G06T13/80 , G06T19/00 , G06T7/55 , G06T7/73 , G06T7/246 , A61B5/00 , A61B5/11 , G06T3/00 , G06N3/08
Abstract: Cardiac features captured via an MRI scan may be tracked and analyzed using a system described herein. The system may receive a plurality of MR slices derived via the MRI scan and present the MR slices in a manner that allows a user to navigate through the MR slices. Responsive to the user selecting one of the MR slices, contextual and global cardiac information associated with the selected slice may be determined and displayed. The contextual information may correspond to the selected slice and the global information may encompass information gathered across the plurality of MR slices. A user may have the ability to navigate between the different display areas and evaluate the health of the heart with both local and global perspectives.
-
公开(公告)号：US20220026514A1
公开(公告)日：2022-01-27
申请号：US16936571
申请日：2020-07-23
Inventor： Zhang Chen , Shanhui Sun , Xiao Chen , Terrence Chen
Abstract: An apparatus for magnetic resonance imaging (MRI) image reconstruction is provided. The apparatus accesses a training set of MRI data for training. The training set can include paired fully sampled data or unpaired fully sampled data. Undersampled MRI data is optimized in an MRI data optimization module to generate reconstructed MRI data. The apparatus builds a discriminative model using the training set and the reconstructed MRI data. During inference, the parameters of the discriminator model are fixed and the discriminator model is used to classify an output of the MRI data optimization model as the reconstructed MRI image.
-
公开(公告)号：US20210161422A1
公开(公告)日：2021-06-03
申请号：US17060860
申请日：2020-10-01
Inventor： Xiao Chen , Shanhui Sun , Zhang Chen , Terrence Chen
IPC: A61B5/055 , A61B5/00 , G06N3/08 , G01R33/561
Abstract: A method includes acquiring initial scout images of a patient's heart, using a neural network to establish a patient specific heart model, and automatically plan imaging planes of the patient specific heart model, performing an accelerated scan of the patient's heart, using the neural network to determine a current location and pose of the patient's heart from the accelerated scan, and to reposition the imaging planes to correspond to the current location and pose of the patient's heart, and using the repositioned imaging planes to perform an acquisition scan and generate an image of the patient's heart from the acquisition scan according to a selected imaging protocol.
-
-
-
-
-
-
-
-
-
Search Results
110
records
(took 0.026 seconds)
