公开(公告)号：US20210132170A1

公开(公告)日：2021-05-06

申请号：US17142475

申请日：2021-01-06

申请人： CORNELL UNIVERSITY

发明人： Yi Wang ,  Zhe Liu ,  Youngwook Kee ,  Alexey Dimov ,  Yan Wen ,  Jingwei Zhang ,  Pascal Spincemaille

IPC分类号： G01R33/56 ,  A61B5/055 ,  G01R33/565 ,  G01R33/24 ,  A61B5/026 ,  A61B5/00

摘要： Exemplary quantitative susceptibility mapping methods, systems and computer-accessible medium can be provided to generate images of tissue magnetism property from complex magnetic resonance imaging data using the Bayesian inference approach, which minimizes a cost function consisting of a data fidelity term and two regularization terms. The data fidelity term is constructed directly from the complex magnetic resonance imaging data. The first prior is constructed from matching structures or information content in known morphology. The second prior is constructed from a region having an approximately homogenous and known susceptibility value and a characteristic feature on anatomic images. The quantitative susceptibility map can be determined by minimizing the cost function. Thus, according to the exemplary embodiment, system, method and computer-accessible medium can be provided for determining magnetic susceptibility information associated with at least one structure.

公开(公告)号：US20180321347A1

公开(公告)日：2018-11-08

申请号：US15943753

申请日：2018-04-03

申请人： CORNELL UNIVERSITY

发明人： Yi Wang ,  Zhe Liu ,  Youngwook Kee ,  Alexey Dimov ,  Yan Wen ,  Jingwei Zhang ,  Pascal Spincemaille

IPC分类号： G01R33/56 ,  A61B5/055 ,  G01R33/48 ,  G01R33/50 ,  G01R33/565

CPC分类号： G01R33/5608 ,  A61B5/055 ,  G01R33/4828 ,  G01R33/50 ,  G01R33/5602 ,  G01R33/56527

摘要： Exemplary quantitative susceptibility mapping methods, systems and computer-accessible medium can be provided to generate images of tissue magnetism property from complex magnetic resonance imaging data using the Bayesian inference approach, which minimizes a cost function consisting of a data fidelity term and two regularization terms. The data fidelity term is constructed directly from the complex magnetic resonance imaging data. The first prior is constructed from matching structures or information content in known morphology. The second prior is constructed from a region having an approximately homogenous and known susceptibility value and a characteristic feature on anatomic images. The quantitative susceptibility map can be determined by minimizing the cost function. Thus, according to the exemplary embodiment, system, method and computer-accessible medium can he provided for determining magnetic susceptibility information associated with at least one structure.

公开(公告)号：US10890641B2

公开(公告)日：2021-01-12

申请号：US15943753

申请日：2018-04-03

申请人： CORNELL UNIVERSITY

发明人： Yi Wang ,  Zhe Liu ,  Youngwook Kee ,  Alexey Dimov ,  Yan Wen ,  Jingwei Zhang ,  Pascal Spincemaille

IPC分类号： G06K9/00 ,  G01R33/56 ,  A61B5/055 ,  G01R33/565 ,  G01R33/24 ,  A61B5/026 ,  A61B5/00 ,  G01R33/50 ,  G01R33/48 ,  A61B5/145

摘要： Exemplary quantitative susceptibility mapping methods, systems and computer-accessible medium can be provided to generate images of tissue magnetism property from complex magnetic resonance imaging data using the Bayesian inference approach, which minimizes a cost function consisting of a data fidelity term and two regularization terms. The data fidelity term is constructed directly from the complex magnetic resonance imaging data. The first prior is constructed from matching structures or information content in known morphology. The second prior is constructed from a region having an approximately homogenous and known susceptibility value and a characteristic feature on anatomic images. The quantitative susceptibility map can be determined by minimizing the cost function. Thus, according to the exemplary embodiment, system, method and computer-accessible medium can be provided for determining magnetic susceptibility information associated with at least one structure.

公开(公告)号：US20230320611A1

公开(公告)日：2023-10-12

申请号：US18042163

申请日：2021-08-19

申请人： Cornell University

发明人： Yi Wang ,  Yan Wen ,  Ramin Jafari ,  Thanh Nguyen ,  Pascal Spincemaille ,  Junghun Cho ,  Qihao Zhang

IPC分类号： A61B5/055 ,  A61B5/00

CPC分类号： A61B5/055 ,  A61B5/0042 ,  A61B5/4872 ,  G06T7/00

摘要： Quantitative susceptibility mapping methods, systems and computer-accessible medium generate images of tissue magnetism property from complex magnetic resonance imaging data using the Bayesian inference approach, which minimizes a cost function comprising of a data fidelity term and regularization terms. The data fidelity term is constructed directly from the multiecho complex magnetic resonance imaging data. The regularization terms include a prior constructed from matching structures or information content in known morphology, and a prior constructed from regions of low susceptibility contrasts characterized on image features. The quantitative susceptibility map can be determined by minimizing the cost function that involves nonlinear functions in modeling the obtained signals, and the corresponding inverse problem is solved using nonconvex optimization using a scaling approach or deep neural network. The nonconvex optimization is also developed for solving other inverse problems of nonlinear signal models in fat-water separation, tissue transport and oxygen extraction fraction.

公开(公告)号：US20230160987A1

公开(公告)日：2023-05-25

申请号：US18151860

申请日：2023-01-09

申请人： CORNELL UNIVERSITY

发明人： Yi Wang ,  Zhe Liu ,  Youngwook Kee ,  Alexey Dimov ,  Yan Wen ,  Jingwei Zhang ,  Pascal Spincemaille

IPC分类号： G01R33/56 ,  A61B5/055 ,  G01R33/565 ,  G01R33/24 ,  A61B5/026 ,  A61B5/00 ,  G06T7/00

CPC分类号： G01R33/5608 ,  A61B5/055 ,  G01R33/56527 ,  G01R33/24 ,  A61B5/0263 ,  A61B5/0042 ,  A61B5/7203 ,  G06T7/0012 ,  G01R33/50

摘要： Exemplary quantitative susceptibility mapping methods, systems and computer-accessible medium can be provided to generate images of tissue magnetism property from complex magnetic resonance imaging data using the Bayesian inference approach, which minimizes a cost function consisting of a data fidelity term and two regularization terms. The data fidelity term is constructed directly from the complex magnetic resonance imaging data. The first prior is constructed from matching structures or information content in known morphology. The second prior is constructed from a region having an approximately homogenous and known susceptibility value and a characteristic feature on anatomic images. The quantitative susceptibility map can be determined by minimizing the cost function. Thus, according to the exemplary embodiment, system, method and computer-accessible medium can be provided for determining magnetic susceptibility information associated with at least one structure.

公开(公告)号：US11635480B2

公开(公告)日：2023-04-25

申请号：US17142475

申请日：2021-01-06

申请人： CORNELL UNIVERSITY

发明人： Yi Wang ,  Zhe Liu ,  Youngwook Kee ,  Alexey Dimov ,  Yan Wen ,  Jingwei Zhang ,  Pascal Spincemaille

IPC分类号： G06K9/00 ,  G01R33/56 ,  A61B5/055 ,  G01R33/565 ,  G01R33/24 ,  A61B5/026 ,  A61B5/00 ,  G06T7/00 ,  G01R33/50 ,  G01R33/48 ,  A61B5/145

摘要： Exemplary quantitative susceptibility mapping methods, systems and computer-accessible medium can be provided to generate images of tissue magnetism property from complex magnetic resonance imaging data using the Bayesian inference approach, which minimizes a cost function consisting of a data fidelity term and two regularization terms. The data fidelity term is constructed directly from the complex magnetic resonance imaging data. The first prior is constructed from matching structures or information content in known morphology. The second prior is constructed from a region having an approximately homogenous and known susceptibility value and a characteristic feature on anatomic images. The quantitative susceptibility map can be determined by minimizing the cost function. Thus, according to the exemplary embodiment, system, method and computer-accessible medium can be provided for determining magnetic susceptibility information associated with at least one structure.