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公开(公告)号：US11270157B2
公开(公告)日：2022-03-08
申请号：US16728086
申请日：2019-12-27
发明人： Yanbo Chen , Yaozong Gao , Yiqiang Zhan
摘要： The present disclosure provides a system and method for classification determination of a structure. The method may include obtaining image data representing a structure of a subject. The method may also include determining a plurality of candidate classifications of the structure and their respective probabilities by inputting the image data into a classification model. The classification model may include a backbone network for determining a backbone feature of the structure, a segmentation network for determining a segmentation feature of the structure, and a density classification network for determining a density feature of the structure. The method may further include determining a target classification of the structure based on at least a part of the probabilities of the plurality of candidate classifications.
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公开(公告)号：US11257586B2
公开(公告)日：2022-02-22
申请号：US16863382
申请日：2020-04-30
发明人： Srikrishna Karanam , Ziyan Wu , Georgios Georgakis
IPC分类号： G06K9/00 , G16H30/40 , G06T7/00 , G06T7/90 , G06T17/00 , G06K9/46 , G06T7/50 , G06T7/70 , G06K9/62 , G06T17/20 , G16H10/60 , G16H30/20 , A61B5/00 , G06K9/52
摘要： Human mesh model recovery may utilize prior knowledge of the hierarchical structural correlation between different parts of a human body. Such structural correlation may be between a root kinematic chain of the human body and a head or limb kinematic chain of the human body. Shape and/or pose parameters relating to the human mesh model may be determined by first determining the parameters associated with the root kinematic chain and then using those parameters to predict the parameters associated with the head or limb kinematic chain. Such a task can be accomplished using a system comprising one or more processors and one or more storage devices storing instructions that, when executed by the one or more processors, cause the one or more processors to implement one or more neural networks trained to perform functions related to the task.
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公开(公告)号：US11244446B2
公开(公告)日：2022-02-08
申请号：US16664690
申请日：2019-10-25
发明人： Ziyan Wu , Shanhui Sun , Arun Innanje
摘要： The present disclosure relates to systems and methods for imaging. The method may include obtaining a real-time representation of a subject. The method may also include determining at least one scanning parameter associated with the subject by automatically processing the representation according to a parameter obtaining model. The method may further include performing a scan on the subject based at least in part on the at least one scanning parameter.
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公开(公告)号：US20210407656A1
公开(公告)日：2021-12-30
申请号：US17469520
申请日：2021-09-08
发明人： JIE-ZHI CHENG , Zaiwen Gong , Zhiqiang He , Yiqiang Zhan , Xiang Sean Zhou
摘要： Method and system for grading a medical image. For example, a system for grading a medical image comprising a grading network configured to provide a grading result corresponding to the medical image based on at least the medical image and/or a list of lesion candidates generated by a lesion identification network.
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公开(公告)号：US20210397886A1
公开(公告)日：2021-12-23
申请号：US16908148
申请日：2020-06-22
发明人： Xiao Chen , Pingjun Chen , Zhang Chen , Terrence Chen , Shanhui Sun
摘要： 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
发明人： Srikrishna Karanam , Ziyan Wu , Terrence Chen
摘要： 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
发明人： Zhang Chen , Shanhui Sun , Terrence Chen
摘要： 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：US20210327057A1
公开(公告)日：2021-10-21
申请号：US17246139
申请日：2021-04-30
发明人： Jianfeng Zhang , Yanli Song , Dijia Wu , Yiqiang Zhan , Xiang Sean Zhou
摘要： Method and system for displaying one or more regions of interest of an original image. For example, a computer-implemented method for displaying one or more regions of interest of an original image includes: obtaining one or more detection results of one or more first regions of interest, each detection result of the one or more detection results corresponding to one first region of interest of the one or more first regions of interest, each detection result including image information and one or more attribute parameters for their corresponding first region of interest; and obtaining one or more attribute parameter thresholds provided by a user in real time, each attribute parameter threshold of the one or more attribute parameter thresholds corresponding to one attribute parameter of the one or more attribute parameters.
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89.发明授权公开(公告)号：US11055855B2
公开(公告)日：2021-07-06
申请号：US16596084
申请日：2019-10-08
发明人： Jianlong Nie , Zhong Xue
摘要： Methods and systems for determining a motion amplitude of an object being scanned. For example, a computer-implemented method for determining a motion amplitude of an object being scanned includes determining an internal parameter set based at least in part on calibrating the scanning apparatus according to a first predetermined algorithm; determining an external parameter set based at least in part on a testing surface and the internal parameter set; determining a mapping relationship between a pixel coordinate system and a world coordinate system based at least in part on the determined internal parameter set and the determined external parameter set; determining a motion amplitude of the object in the pixel coordinate system; and determining a motion amplitude of the object in the world coordinate system based at least in part on the determined mapping relationship and the motion amplitude of the object in the pixel coordinate system.
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公开(公告)号：US20210199742A1
公开(公告)日：2021-07-01
申请号：US17137489
申请日：2020-12-30
发明人： Xuyang LYU , Shu LIAO
IPC分类号： G01R33/56 , G01R33/561
摘要： A method for MRI reconstruction is provided. The method may include obtaining a plurality of sub-sampled images of a subject. The plurality of sub-sampled images may include a first sub-sampled image of the subject and one or more second sub-sampled images of the subject. The first sub-sampled image may be generated using a first MRI sequence and a first sub-sampling rate. Each of the one or more second sub-sampled images may be generated using a second MRI sequence and a second sub-sampling rate. The second sub-sampling rate may be smaller than the first sub-sampling rate. The method may include obtaining an image reconstruction model having been trained according to a machine learning technique. The method may further include generating a first full image of the subject corresponding to the first MRI sequence based on the first sub-sampled image, the one or more second sub-sampled images, and the image reconstruction model.
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