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公开(公告)号：US11051772B2
公开(公告)日：2021-07-06
申请号：US16294438
申请日：2019-03-06
Applicant: Rensselaer Polytechnic Institute
Inventor： Daniel David Harrison , Ge Wang
Abstract: Systems and method for performing X-ray computed tomography (CT) that can improve spectral separation and decrease motion artifacts without increasing radiation dose are provided. The systems and method can be used with either a kVp-switching source or a single-kVp source. When used with a kVp-switching source, an absorption grating and a filter grating can be disposed between the X-ray source and the sample to be imaged. Relative motion of the filter and absorption gratings can by synchronized to the kVp switching frequency of the X-ray source. When used with a single-kVp source, a combination of absorption and filter gratings can be used and can be driven in an oscillation movement that is optimized for a single-kVp X-ray source. With a single-kVp source, the absorption grating can also be omitted and the filter grating can remain stationary.
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公开(公告)号：US10970886B2
公开(公告)日：2021-04-06
申请号：US16597250
申请日：2019-10-09
Applicant: University of Iowa Research Foundation , Shandong University , Shandong Provincial Chest Hospital , Rensselaer Polytechnic Institute
Inventor： Wenxiang Cong , Ye Yangbo , Ge Wang , Shuwei Mao , Yingmei Wang
Abstract: The disclosed apparatus, systems and methods relate to a framelet-based iterative algorithm for polychromatic CT which can reconstruct two components using a single scan. The algorithm can have various steps including a scaled-gradient descent step of constant or variant step sizes; a non-negativity step; a soft thresholding step; and a color reconstruction step.
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公开(公告)号：US20210035340A1
公开(公告)日：2021-02-04
申请号：US16969072
申请日：2019-02-11
Applicant: RENSSELAER POLYTECHNIC INSTITUTE
Inventor： Ge Wang , Daniel David Harrison , Xun Jia , Klaus Mueller
Abstract: In some embodiments, a method of machine learning includes identifying, by an auto encoder network, a simulator feature based, at least in part, on a received first simulator data set and an emulator feature based, at least in part, on a received first emulator data set. The method further includes determining, by a synthesis control circuitry, a synthesized feature based, at least in part, on the simulator feature and based, at least in part, on the emulator feature; and generating, by the auto encoder network, an intermediate data set based, at least in part, on a second simulator data set and including the synthesized feature. Some embodiments of the method further include determining, by a generative artificial neural network, a synthesized data set based, at least in part, on the intermediate data set and based, at least in part, on an objective function.
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公开(公告)号：US10548543B2
公开(公告)日：2020-02-04
申请号：US15538376
申请日：2015-12-22
Applicant: RENSSELAER POLYTECHNIC INSTITUTE
Inventor： Ge Wang , Yan Xi , Wenxiang Cong , Zaifeng Shi
Abstract: Novel and advantageous methods and systems for performing spectral computed tomography are provided. An edge-on detector, such as a silicon strip detector, can be used to receive X-rays after passing through a sample to be imaged. An energy resolving process can be performed on the collected X-ray radiation. The CT scanner can have third-generation or fourth-generation geometry.
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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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Patent Agency Ranking
66.发明授权公开(公告)号：US12266162B2
公开(公告)日：2025-04-01
申请号：US17766365
申请日：2019-10-08
Applicant: RENSSELAER POLYTECHNIC INSTITUTE
Inventor： Seung Wook Lee , Seho Lee , Ge Wang
Abstract: The present disclosure relates to an apparatus for enhancing contrast sensitivity and resolution in a grating interferometer by machine learning, which can improve both image contrast sensitivity and spatial resolution in a grating interferometer by machine learning, the apparatus including: an image acquisition unit; a numerical phantom generation unit, a convolution layer generation unit to extract features from input data; an activation function application calculation unit that can apply a rectified linear activation function to an output value of the convolution calculation to perform smooth repetitive machine learning; a CNN repetitive machine learning unit that corrects a convolution calculation factor while repeatedly performing forward propagation and backward propagation processes; and an image matching output unit that matches and outputs features extracted by repetitive machine learning of the CNN repetitive machine learning unit.
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67.发明公开公开(公告)号：US20240046629A1
公开(公告)日：2024-02-08
申请号：US17766365
申请日：2019-10-08
Applicant: RENSSELAER POLYTECHNIC INSTITUTE
Inventor： Seung Wook Lee , Seho Lee , Ge Wang
CPC classification number: G06V10/82 , G06V10/751 , G02B6/29353 , G06V2201/03
Abstract: The present disclosure relates to an apparatus for enhancing contrast sensitivity and resolution in a grating interferometer by machine learning, which can improve both image contrast sensitivity and spatial resolution in a grating interferometer by machine learning, the apparatus including: an image acquisition unit; a numerical phantom generation unit, a convolution layer generation unit to extract features from input data; an activation function application calculation unit that can apply a rectified linear activation function to an output value of the convolution calculation to perform smooth repetitive machine learning; a CNN repetitive machine learning unit that corrects a convolution calculation factor while repeatedly performing forward propagation and backward propagation processes; and an image matching output unit that matches and outputs features extracted by repetitive machine learning of the CNN repetitive machine learning unit.
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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：US11686863B2
公开(公告)日：2023-06-27
申请号：US17896279
申请日：2022-08-26
Applicant: Rensselaer Polytechnic Institute
Inventor： Ge Wang , Ruibin Feng , David Rundle
CPC classification number: G01T1/17 , G01T1/18 , G06T7/0012 , A61B6/4241 , G06T2207/10116 , G06T2207/20081 , G06T2207/20084 , G06T2207/30004 , G06T2207/30242
Abstract: A neural network based corrector for photon counting detectors is described. A method for photon count correction includes receiving, by a trained artificial neural network (ANN), a detected photon count from a photon counting detector. The detected photon count corresponds to an attenuated energy spectrum. The attenuated energy spectrum is related to characteristics of an imaging object and is based, at least in part, on an incident energy spectrum. The method further includes correcting, by the trained ANN, the detected photon count to produce a corrected photon count. The method may include reconstructing, by image reconstruction circuitry, an image based, at least in part, on the corrected photon count.
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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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