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公开(公告)号：US20190244399A1
公开(公告)日：2019-08-08
申请号：US16257769
申请日：2019-01-25
申请人： Guobin LI , Nan LIU , Xiaoqian HUANG , Shu LIAO , SHANGHAI UNITED IMAGING HEALTHCARE CO., LTD. , SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.
发明人： Guobin LI , Nan LIU , Xiaoqian HUANG , Shu LIAO
CPC分类号： G06T11/008 , A61B5/055 , A61B5/7257 , A61B5/7267 , A61B2576/00 , G01R33/5608 , G01R33/5611 , G01R33/56509 , G01R33/56545 , G06T5/002 , G06T5/50 , G06T11/006 , G06T2207/10088 , G06T2207/20081 , G06T2207/20221
摘要： The present disclosure is related to systems and methods for image processing. The method may include obtaining a first set of image data. The method may also include generating a second set of image data by processing, based on a trained machine learning model, the first set of image data. The second set of image data may have a relatively high resolution and/or a relatively low level of artifacts with respect to the first set of image data. The method may further include generating a target image by performing a weighted fusion on the first set of image data and the second set of image data.
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公开(公告)号：US20200342637A1
公开(公告)日：2020-10-29
申请号：US16858803
申请日：2020-04-27
发明人： Yang ZHANG , Shu LIAO , Liuchun HE , Zilin DENG
摘要： A system for PET image reconstruction is provided. The system may obtain PET data of a subject. The PET data may be associated with a plurality of coincidence events, which includes scattering events. The system may also generate a preliminary scatter sinogram relating to the scattering events based on the PET data. The system may also generate a target scatter sinogram relating to the scattering events by applying a scatter sinogram generator based on the preliminary scatter sinogram. The target scatter sinogram may have a higher image quality than the preliminary scatter sinogram. The system may further reconstruct a target PET image of the subject based on the PET data and the target scatter sinogram.
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公开(公告)号：US20220349974A1
公开(公告)日：2022-11-03
申请号：US17813329
申请日：2022-07-18
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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公开(公告)号：US20230206517A1
公开(公告)日：2023-06-29
申请号：US18175492
申请日：2023-02-27
发明人： Yang ZHANG , Shu LIAO , Liuchun HE , Zilin DENG
CPC分类号： G06T11/005 , G06T7/0012 , G06T2207/10104 , G06T2207/20081
摘要： A system for PET image reconstruction is provided. The system may obtain PET data of a subject. The PET data may be associated with a plurality of coincidence events, which includes scattering events. The system may also generate a preliminary scatter sinogram relating to the scattering events based on the PET data. The system may also generate a target scatter sinogram relating to the scattering events by applying a scatter sinogram generator based on the preliminary scatter sinogram. The target scatter sinogram may have a higher image quality than the preliminary scatter sinogram. The system may further reconstruct a target PET image of the subject based on the PET data and the target scatter sinogram.
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公开(公告)号：US20220172382A1
公开(公告)日：2022-06-02
申请号：US17651806
申请日：2022-02-20
发明人： Shu LIAO , Yunhao GE , Dongming WEI
摘要： The present disclosure is related to systems and methods for image processing. The method includes obtaining a first image of a first modality. The method includes generating a second image of a second modality by processing, based on a trained machine learning model, the first image. The second modality may be different from the first modality.
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公开(公告)号：US20230154070A1
公开(公告)日：2023-05-18
申请号：US18157794
申请日：2023-01-20
发明人： Xiaoqian HUANG , Shu LIAO
CPC分类号： G06T11/006 , G16H30/40 , A61B5/055 , A61B5/7267 , G06N3/08
摘要： A system for Magnetic Resonance Imaging (MRI) is provided. The system may obtain at least one training sample each of which includes full MRI data. The system may also obtain a preliminary subsampling model and a preliminary MRI reconstruction model. The system may further generate a subsampling model corresponding to an MRI reconstruction model by jointly training the preliminary subsampling model and the preliminary MRI reconstruction model using the at least one training sample. The subsampling model may be the trained preliminary subsampling model, and the MRI reconstruction model may be at least a portion of the trained preliminary MRI reconstruction model.
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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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公开(公告)号：US20200211209A1
公开(公告)日：2020-07-02
申请号：US16729303
申请日：2019-12-28
发明人： Shu LIAO , Yunhao GE , Dongming WEI
摘要： The present disclosure is related to systems and methods for image processing. The method includes obtaining a first image of a first modality. The method includes generating a second image of a second modality by processing, based on a trained machine learning model, the first image. The second modality may be different from the first modality.
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公开(公告)号：US20210065413A1
公开(公告)日：2021-03-04
申请号：US17002817
申请日：2020-08-26
发明人： Xiaoqian HUANG , Shu LIAO
摘要： A system for Magnetic Resonance Imaging (MRI) is provided. The system may obtain at least one training sample each of which includes full MRI data. The system may also obtain a preliminary subsampling model and a preliminary MRI reconstruction model. The system may further generate a subsampling model corresponding to an MRI reconstruction model by jointly training the preliminary subsampling model and the preliminary MRI reconstruction model using the at least one training sample. The subsampling model may be the trained preliminary subsampling model, and the MRI reconstruction model may be at least a portion of the trained preliminary MRI reconstruction model.
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