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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
发明人： Ziyan Wu , Srikrishna Karanam , Arun Innanje
摘要： 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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公开(公告)号：US20230079164A1
公开(公告)日：2023-03-16
申请号：US17475534
申请日：2021-09-15
发明人： Shanhui Sun , Zhang Chen , Xiao Chen , Terrence Chen , Junshen Xu
摘要： 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：US11557391B2
公开(公告)日：2023-01-17
申请号：US16995446
申请日：2020-08-17
IPC分类号： 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
摘要： 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
发明人： Ziyan Wu , Srikrishna Karanam , Meng Zheng , Abhishek Sharma , Ren Li
摘要： 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：US20220392018A1
公开(公告)日：2022-12-08
申请号：US17340635
申请日：2021-06-07
发明人： Xiao Chen , Shuo Han , Zhang Chen , Shanhui Sun , Terrence Chen
摘要： 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：US20220309663A1
公开(公告)日：2022-09-29
申请号：US17806269
申请日：2022-06-09
发明人： Minqing ZHANG , Qin LIU , Dijia WU , Yiqiang ZHAN , Xiang Sean ZHOU
摘要： Systems and methods for ossification center detection (OCD) and bone age assessment (BAA) may be provided. The method may include obtaining a bone age image of a subject. The method may include generating a normalized bone age image by preprocessing the bone age image. The method may include determining, based on the normalized bone age image, positions of a plurality of ossification centers using an ossification center localization (OCL) model. The method may include estimating, based on the normalized bone age image and information related to the positions of the plurality of ossification centers, a bone age of the subject using a bone age assessment (BAA) model.
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公开(公告)号：US20220284687A1
公开(公告)日：2022-09-08
申请号：US17664422
申请日：2022-05-22
发明人： Miaofei HAN , Yaozong GAO , Yu ZHANG , Yiqiang ZHAN
IPC分类号： G06V10/22 , G06T7/62 , G06T7/11 , G06T7/149 , G16H50/50 , G16H50/30 , G16H50/20 , G16H30/40 , A61B5/107 , G06K9/62 , G06N3/04 , G06V30/24
摘要： A system for image segmentation is provided. The system may obtain a target image including an ROI, and segment a preliminary region representative of the ROI from the target image using a first ROI segmentation model corresponding to a first image resolution. The system may segment a target region representative of the ROI from the preliminary region using a second ROI segmentation model corresponding to a second image resolution. At least one model of the first and second ROI segmentation models may at least include a first convolutional layer and a second convolutional layer downstream to the first convolutional layer. A count of input channels of the first convolutional layer may be greater than a count of output channels of the first convolutional layer, and a count of input channels of the second convolutional layer may be smaller than a count of output channels of the second convolutional layer.
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公开(公告)号：US11436720B2
公开(公告)日：2022-09-06
申请号：US16729249
申请日：2019-12-27
发明人： Zaiwen Gong , Hengze Zhan , Jie-Zhi Cheng , Yiqiang Zhan , Jibing Wu , Xiang Sean Zhou
摘要： The present disclosure may provide a method. The method may include processing an image of a subject using a detection model to generate one or more detection results corresponding to one or more objects in the image; and generating an image metric of the image based on the one or more detection results corresponding to the one or more objects.
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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
发明人： Yimo Guo , Xiao Chen , Shanhui Sun , Terrence Chen
摘要： 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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公开(公告)号：US11288841B2
公开(公告)日：2022-03-29
申请号：US16656511
申请日：2019-10-17
发明人： Ziyan Wu , Srikrishna Karanam
IPC分类号： G06T7/73
摘要： 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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