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公开(公告)号：US20230169659A1
公开(公告)日：2023-06-01
申请号：US17538282
申请日：2021-11-30
Inventor： Xiao Chen , Xiaoling Hu , Zhang Chen , Yikang Liu , Terrence Chen , Shanhui Sun
CPC classification number: G06T7/11 , G06T7/149 , G06T3/0093 , G06T3/0006 , G06T7/246 , G06T2207/20084 , G06T2207/20081 , G06T2207/20124 , G06T2207/30048 , G06T2207/10088
Abstract: Described herein are systems, methods, and instrumentalities associated with segmenting and/or determining the shape of an anatomical structure. An artificial neural network (ANN) is used to perform these tasks based on a statistical shape model of the anatomical structure. The ANN is trained by evaluating and backpropagating multiple losses associated with shape estimation and segmentation mask generation. The model obtained using these techniques may be used for different clinical purposes including, for example, motion estimation and motion tracking.
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公开(公告)号：US20230138380A1
公开(公告)日：2023-05-04
申请号：US17513493
申请日：2021-10-28
Inventor： Zhang Chen , Xiao Chen , Yikang Liu , Terrence Chen , Shanhui Sun
IPC: G06K9/62 , G06T7/00 , G06T5/00 , G06T3/40 , G06K9/00 , G06T11/00 , G06N3/08 , G16H30/20 , G01R33/56
Abstract: A neural network system implements a model for generating an output image based on a received input image. The model is learned through a training process during which parameters associated with the model are adjusted so as to maximize a difference between a first image predicted using first parameter values of the model and a second image predicted using second parameter values of the model, and to minimize a difference between the second image and a ground truth image. During a first iteration of the training process the first image is predicted and during a second iteration the second image is predicted. The first parameter values are obtained during the first iteration by minimizing a difference between the first image and the ground truth image, and the second parameter values are obtained during the second iteration by maximizing the difference between the first image and the second image.
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公开(公告)号：US20230079164A1
公开(公告)日：2023-03-16
申请号：US17475534
申请日：2021-09-15
Inventor： Shanhui Sun , Zhang Chen , Xiao Chen , Terrence Chen , Junshen Xu
Abstract: Deep learning based systems, methods, and instrumentalities are described herein for registering images from a same imaging modality and different imaging modalities. Transformation parameters associated with the image registration task are determined using a neural ordinary differential equation (ODE) network that comprises multiple layers, each configured to determine a respective gradient update for the transformation parameters based on a current state of the transformation parameters received by the layer. The gradient updates determined by the multiple ODE layers are then integrated and applied to initial values of the transformation parameters to obtain final parameters for completing the image registration task. The operations of the ODE network may be facilitated by a feature extraction network pre-trained to determine content features shared by the input images. The input images may be resampled into different scales, which are then processed by the ODE network iteratively to improve the efficiency of the ODE operations.
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公开(公告)号：US20220392018A1
公开(公告)日：2022-12-08
申请号：US17340635
申请日：2021-06-07
Inventor： Xiao Chen , Shuo Han , Zhang Chen , Shanhui Sun , Terrence Chen
Abstract: Motion contaminated magnetic resonance (MR) images for training an artificial neural network to remove motion artifacts from the MR images are difficult to obtain. Described herein are systems, methods, and instrumentalities for injecting motion artifacts into clean MR images and using the artificially contaminated images for machine learning and neural network training. The motion contaminated MR images may be created based on clean source MR images that are associated with multiple physiological cycles of a scanned object, and by deriving MR data segments for the multiple physiological cycles based on the source MR images. The MR data segments thus derived may be combined to obtain a simulated MR data set, from which one or more target MR images may be generated to exhibit a motion artifact. The motion artifact may be created by manipulating the source MR images and/or controlling the manner in which the MR data set or the target MR images are generated.
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公开(公告)号：US20220122259A1
公开(公告)日：2022-04-21
申请号：US17076641
申请日：2020-10-21
Inventor： Yimo Guo , Xiao Chen , Shanhui Sun , Terrence Chen
Abstract: A bullseyes plot may be generated based on cardiac magnetic resonance imaging (CMRI) to facilitate the diagnosis and treatment of heart diseases. Described herein are systems, methods, and instrumentalities associated with bullseyes plot generation. A plurality of myocardial segments may be obtained for constructing the bullseye plot based on landmark points detected in short-axis and long-axis magnetic resonance (MR) slices of the heart and by arranging the short-axis MR slices sequentially in accordance with the order in which the slices are generated during the CMRI. The sequential order of the short-axis MR slices may be determined utilizing projected locations of the short-axis MR slices on a long-axis MR slice and respective distances of the projected locations to a landmark point of the long-axis MR slice. The myocardium and/or landmark points may be identified in the short-axis and/or long-axis MR slices using artificial neural networks.
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Patent Agency Ranking
公开(公告)号：US20210397886A1
公开(公告)日：2021-12-23
申请号：US16908148
申请日：2020-06-22
Inventor： Xiao Chen , Pingjun Chen , Zhang Chen , Terrence Chen , Shanhui Sun
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 utilizing pre-learned knowledge of the anatomy of the anatomical structure. The anatomical knowledge may be learned via a variational autoencoder, which may then be used to optimize the parameters of a motion estimation neural network system such that, when performing motion estimation for the anatomical structure, the motion estimation neural network system may produce results that conform with the underlying anatomy of anatomical structure.
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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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公开(公告)号：US11199602B2
公开(公告)日：2021-12-14
申请号：US16555781
申请日：2019-08-29
Inventor： Zhang Chen , Shanhui Sun , Terrence Chen
Abstract: Methods and systems for acquiring a visualization of a target. For example, a computer-implemented method for acquiring a visualization of a target includes: generating a first sampling mask; acquiring first k-space data of the target at a first phase using the first sampling mask; generating a first image of the target based at least in part on the first k-space data; generating a second sampling mask using a model based on at least one selected from the first sampling mask, the first k-space data, and the first image; acquiring second k-space data of the target at a second phase using the second sampling mask; and generating a second image of the target based at least in part on the second k-space data.
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公开(公告)号：US20210166445A1
公开(公告)日：2021-06-03
申请号：US16699540
申请日：2019-11-29
Inventor： Puyang Wang , Zhang Chen , Shanhui Sun , Terrence Chen
Abstract: A system for reconstructing magnetic resonance images includes a processor that is configured to obtain, from a magnetic resonance scanner, sub-sampled k-space data; apply an inverse fast fourier transform to the sub-sampled k-space data to generate a preliminary image; and process the preliminary image via a trained cascaded recurrent neural network to reconstruct a magnetic resonance image.
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90.发明申请公开(公告)号：US20210165064A1
公开(公告)日：2021-06-03
申请号：US17060988
申请日：2020-10-01
Inventor： Zhang Chen , Xiao Chen , Shanhui Sun , Terrence Chen
IPC: G01R33/563 , G06N3/08 , G01R33/36
Abstract: A method includes using fully sampled retro cine data to train an algorithm, and applying the trained algorithm to real time MR cine data to yield reconstructed MR images.
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