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公开(公告)号：US20210000438A1
公开(公告)日：2021-01-07
申请号：US16978258
申请日：2019-03-06
Applicant: RENSSELAER POLYTECHNIC INSTITUTE
Inventor： Ge Wang , Lars Arne Gjesteby , Qingsong Yang , Hongming Shan
Abstract: A deep neural network for metal artifact reduction is described. A method for computed tomography (CT) metal artifact reduction (MAR) includes generating, by a projection completion circuitry, an intermediate CT image data based, at least in part, on input CT projection data. The intermediate CT image data is configured to include relatively fewer artifacts than an uncorrected CT image reconstructed from the input CT projection data. The method further includes generating, by an artificial neural network (ANN), CT output image data based, at least in part, on the intermediate CT image data. The CT output image data is configured to include relatively fewer artifacts compared to the intermediate CT image data. The method may further include generating, by detail image circuitry, detail CT image data based, at least in part, on input CT image data. The CT output image data is generated based, at least in part, on the detail CT image data.
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公开(公告)号：US20200261030A1
公开(公告)日：2020-08-20
申请号：US16761543
申请日：2018-11-06
Applicant: RENSSELAER POLYTECHNIC INSTITUTE
Inventor： Ge Wang , Wenxiang Cong , Qingsong Yang , Guang Li
Abstract: A stationary in-vivo grating-enabled micro-CT (computed tomography) architecture (SIGMA) system includes CT scanner control circuitry and a number of imaging chains. Each imaging chain includes an x-ray source array, a phase grating, an analyzer grating and a detector array. Each imaging chain is stationary and each x-ray source array includes a plurality of x-ray source elements. Each imaging chain has a centerline, the centerlines of the number of imaging chains intersect at a center point and a first angle between the centerlines of a first adjacent pair of imaging chains equals a second angle between the centerlines of a second adjacent pair of imaging chains. A plurality of selected x-ray source elements of a first x-ray source array is configured to emit a plurality of x-ray beams in a multiplexing fashion.
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公开(公告)号：US11423591B2
公开(公告)日：2022-08-23
申请号：US16481298
申请日：2017-05-23
Applicant: RENSSELAER POLYTECHNIC INSTITUTE
Inventor： Ge Wang , Wenxiang Cong , Qingsong Yang
Abstract: Systems and methods for reconstructing images for computed tomography are provided. Image reconstruction can be based on a realistic polychromatic physical model, and can include use of both an analytical algorithm and a single-variable optimization method. The optimization method can be used to solve the non-linear polychromatic X-ray integral model in the projection domain, resulting in an accurate decomposition for sinograms of two physical basis components.
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公开(公告)号：US11382574B2
公开(公告)日：2022-07-12
申请号：US16761543
申请日：2018-11-06
Applicant: RENSSELAER POLYTECHNIC INSTITUTE
Inventor： Ge Wang , Wenxiang Cong , Qingsong Yang , Guang Li
IPC: A61B6/03 , A61B6/00 , G01N23/041
Abstract: A stationary in-vivo grating-enabled micro-CT (computed tomography) architecture (SIGMA) system includes CT scanner control circuitry and a number of imaging chains. Each imaging chain includes an x-ray source array, a phase grating, an analyzer grating and a detector array. Each imaging chain is stationary and each x-ray source array includes a plurality of x-ray source elements. Each imaging chain has a centerline, the centerlines of the number of imaging chains intersect at a center point and a first angle between the centerlines of a first adjacent pair of imaging chains equals a second angle between the centerlines of a second adjacent pair of imaging chains. A plurality of selected x-ray source elements of a first x-ray source array is configured to emit a plurality of x-ray beams in a multiplexing fashion.
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公开(公告)号：US12154193B2
公开(公告)日：2024-11-26
申请号：US17859061
申请日：2022-07-07
Applicant: RENSSELAER POLYTECHNIC INSTITUTE
Inventor： Ge Wang , Wenxiang Cong , Qingsong Yang
Abstract: Systems and methods for reconstructing images for computed tomography are provided. Image reconstruction can be based on a realistic polychromatic physical model, and can include use of both an analytical algorithm and a single-variable optimization method. The optimization method can be used to solve the non-linear polychromatic X-ray integral model in the projection domain, resulting in an accurate decomposition for sinograms of two physical basis components.
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Patent Agency Ranking
公开(公告)号：US11589834B2
公开(公告)日：2023-02-28
申请号：US16978258
申请日：2019-03-06
Applicant: RENSSELAER POLYTECHNIC INSTITUTE
Inventor： Ge Wang , Lars Arne Gjesteby , Qingsong Yang , Hongming Shan
Abstract: A deep neural network for metal artifact reduction is described. A method for computed tomography (CT) metal artifact reduction (MAR) includes generating, by a projection completion circuitry, an intermediate CT image data based, at least in part, on input CT projection data. The intermediate CT image data is configured to include relatively fewer artifacts than an uncorrected CT image reconstructed from the input CT projection data. The method further includes generating, by an artificial neural network (ANN), CT output image data based, at least in part, on the intermediate CT image data. The CT output image data is configured to include relatively fewer artifacts compared to the intermediate CT image data. The method may further include generating, by detail image circuitry, detail CT image data based, at least in part, on input CT image data. The CT output image data is generated based, at least in part, on the detail CT image data.
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公开(公告)号：US10537299B2
公开(公告)日：2020-01-21
申请号：US15579394
申请日：2016-06-06
Applicant: RENSSELAER POLYTECHNIC INSTITUTE
Inventor： Ge Wang , Qingsong Yang , Wenxiang Cong
Abstract: Systems and methods for determining an attenuation sinogram for a time-of-flight (TOF) positron emission tomography (PET) scan using only TOF PET data, and including use of the total amount of tracer provided to the subject of the TOF PET scan, are provided. The total amount of injected tracer can be used to determine the otherwise unknown constant shift present when an attenuation sinogram is estimated using the gradient of the attenuation sinogram. The attenuation sinogram can therefore be accurately and stably determined without any additional knowledge on the attenuation sinogram or map.
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公开(公告)号：US10970887B2
公开(公告)日：2021-04-06
申请号：US16312704
申请日：2017-06-26
Applicant: RENSSELAER POLYTECHNIC INSTITUTE
Inventor： Ge Wang , Wenxiang Cong , Qingsong Yang
Abstract: Tomographic/tomosynthetic image reconstruction systems and methods in the framework of machine learning, such as deep learning, are provided. A machine learning algorithm can be used to obtain an improved tomographic image from raw data, processed data, or a preliminarily reconstructed intermediate image for biomedical imaging or any other imaging purpose. In certain cases, a single, conventional, non-deep-learning algorithm can be used on raw imaging data to obtain an initial image, and then a deep learning algorithm can be used on the initial image to obtain a final reconstructed image. All machine learning methods and systems for tomographic image reconstruction are covered, except for use of a single shallow network (three layers or less) for image reconstruction.
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公开(公告)号：US11872070B2
公开(公告)日：2024-01-16
申请号：US18104925
申请日：2023-02-02
Applicant: Rensselaer Polytechnic Institute
Inventor： Ge Wang , Lars Arne Gjesteby , Qingsong Yang , Hongming Shan
CPC classification number: A61B6/5258 , A61B6/032 , A61B6/5205 , G06N3/084 , G06N5/046 , G06T7/0012 , G06T11/008 , G06T2207/20084
Abstract: A deep neural network for metal artifact reduction is described. A method for computed tomography (CT) metal artifact reduction (MAR) includes receiving a first CT image data; receiving a second CT image data; and generating, by an artificial neural network (ANN), CT output image data configured to include fewer artifacts compared to the first and second CT image data. The ANN includes at least two parallel CT image data streams and a CT output image data stream. A first of the at least two parallel CT image data streams is based, at least in part, on the first CT image data, a second of the at least two parallel CT image data stream is based, at least in part, on the second CT image data. The CT output image data stream is based, at least in part, on respective outputs of the at least two parallel CT image data streams.
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公开(公告)号：US20230181141A1
公开(公告)日：2023-06-15
申请号：US18104925
申请日：2023-02-02
Applicant: Rensselaer Polytechnic Institute
Inventor： Ge Wang , Lars Arne Gjesteby , Qingsong Yang , Hongming Shan
CPC classification number: A61B6/5258 , A61B6/032 , A61B6/5205 , G06N3/084 , G06N5/046 , G06T11/008 , G06T7/0012 , G06T2207/20084
Abstract: A deep neural network for metal artifact reduction is described. A method for computed tomography (CT) metal artifact reduction (MAR) includes receiving a first CT image data; receiving a second CT image data; and generating, by an artificial neural network (ANN), CT output image data configured to include fewer artifacts compared to the first and second CT image data. The ANN includes at least two parallel CT image data streams and a CT output image data stream. A first of the at least two parallel CT image data streams is based, at least in part, on the first CT image data, a second of the at least two parallel CT image data stream is based, at least in part, on the second CT image data. The CT output image data stream is based, at least in part, on respective outputs of the at least two parallel CT image data streams.
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