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    SYSTEM AND METHOD OF ACCURATE QUANTITATIVE MAPPING OF BIOPHYSICAL PARAMETERS FROM MRI DATA
    1.
    发明公开
    SYSTEM AND METHOD OF ACCURATE QUANTITATIVE MAPPING OF BIOPHYSICAL PARAMETERS FROM MRI DATA 审中-公开

    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.

    System and method of robust quantitative susceptibility mapping
    2.
    发明授权
    System and method of robust quantitative susceptibility mapping 有权

    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.

    Method for segmenting objects in images
    3.
    发明授权
    Method for segmenting objects in images 有权
    分割图像中物体的方法

    公开(公告)号：US08831312B2

    公开(公告)日：2014-09-09

    申请号：US13748292

    申请日：2013-01-23

    申请人： Cornell University

    发明人： Yi Wang ,  Noel C. F. Codella ,  Hae-Yeou Lee

    IPC分类号： G06K9/00

    CPC分类号： G06T7/0012 ,  G06T7/11 ,  G06T7/174 ,  G06T7/62 ,  G06T2207/10072 ,  G06T2207/10088 ,  G06T2207/30048

    摘要： A method for identifying an attribute of an object represented in an image comprising data defining a predetermined spatial granulation for resolving the object, where the object is in contact with another object. In an embodiment, the method comprises identifying data whose values indicate they correspond to locations completely within the object, determining a contribution to the attribute provided by the data, and identifying additional data whose values indicate they are not completely within the object. The method next interpolates second contributions to the attribute from the values of the additional data and finds the attribute of the object from the first contribution and second contributions. The attribute may be, for example, a volume, and the values may correspond, for example, to intensity.

    摘要翻译： 一种用于识别在图像中表示的对象的属性的方法，包括定义用于解析对象的预定空间粒度的数据，其中对象与另一对象接触。 在一个实施例中，该方法包括识别其值表示其对应于完全在对象内的位置的数据，确定对由该数据提供的属性的贡献，以及识别其值表示其不完全在对象内的附加数据。 该方法接着从附加数据的值中插入属性的第二个贡献，并从第一个贡献和第二个贡献中找到对象的属性。 属性可以是例如音量，并且该值可以对应于例如强度。

    SYSTEM AND METHOD OF ROBUST QUANTITATIVE SUSCEPTIBILITY MAPPING
    6.
    发明申请
    SYSTEM AND METHOD OF ROBUST QUANTITATIVE SUSCEPTIBILITY MAPPING 有权

    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.

    SYSTEM AND METHOD OF ROBUST QUANTITATIVE SUSCEPTIBILITY MAPPING
    7.
    发明申请
    SYSTEM AND METHOD OF ROBUST QUANTITATIVE SUSCEPTIBILITY MAPPING 审中-公开

    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.