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    Robust Anatomy Detection Through Local Voting And Prediction
    1.
    发明申请
    Robust Anatomy Detection Through Local Voting And Prediction 有权
    通过局部投票和预测进行强大的解剖检测

    公开(公告)号：US20090161937A1

    公开(公告)日：2009-06-25

    申请号：US12334898

    申请日：2008-12-15

    申请人： Zhigang Peng ,  Yiqiang Zhan ,  Xiang Zhou ,  Arun Krishnan

    发明人： Zhigang Peng ,  Yiqiang Zhan ,  Xiang Zhou ,  Arun Krishnan

    IPC分类号： G06K9/00

    CPC分类号： A61B6/032 ,  A61B6/469 ,  A61B6/488 ,  G06K9/3233 ,  G06K2209/05 ,  G06T7/11 ,  G06T7/73 ,  G06T2207/10081 ,  G06T2207/30048

    摘要： A method for performing a medical imaging study includes acquiring a preliminary scan. A set of local feature candidates is automatically detected from the preliminary scan. The accuracy of each local feature candidate is assessed using multiple combinations of the other local feature candidates and removing a local feature candidate that is assessed to have the lowest accuracy. The assessing and removing steps are repeated until only a predetermined number of local feature candidates remain. A region of interest (ROI) is located from within the preliminary scan based on the remaining predetermined number of local feature candidates. A medical imaging study is performed based on the location of the ROI within the preliminary scan.

    摘要翻译： 执行医学成像研究的方法包括获取初步扫描。 从初步扫描中自动检测一组本地特征候选。 使用其他本地特征候选者的多个组合来评估每个本地特征候选者的准确性，并且去除被评估为具有最低精度的局部特征候选。 重复评估和去除步骤，直到仅保留预定数量的局部特征候选。 感兴趣区域（ROI）基于剩余的预定数量的局部特征候选位于初步扫描内。 基于初步扫描中ROI的位置执行医学成像研究。

    Automatic Detection of Lymph Nodes
    2.
    发明申请
    Automatic Detection of Lymph Nodes 有权
    自动检测淋巴结

    公开(公告)号：US20080298662A1

    公开(公告)日：2008-12-04

    申请号：US12121865

    申请日：2008-05-16

    申请人： Senthil Periaswamy ,  Xiang Zhou ,  Yiqiang Zhan ,  Arun Krishnan

    发明人： Senthil Periaswamy ,  Xiang Zhou ,  Yiqiang Zhan ,  Arun Krishnan

    IPC分类号： G06K9/80

    CPC分类号： G06T7/0012 ,  G06T7/62 ,  G06T7/68 ,  G06T2207/30101

    摘要： A method for detecting lymph nodes in a medical image includes receiving image data. One or more regions of interest are detected from within the received image data. One or more lymph node candidates are identified using a set of predefined parameters that is particular to the detected region of interest where each lymph node candidate is located. The identifying unit may identify the one or more lymph node candidates by performing DGFR processing. The method may also include receiving user-provided adjustments to the predefined parameters that are particular to the detected regions of interest and identifying the lymph node candidates based on the adjusted parameters. The lymph node candidates identified based on the adjusted parameters may be displayed along with the image data in real-time as the adjustments are provided.

    摘要翻译： 用于检测医学图像中的淋巴结的方法包括接收图像数据。 从所接收的图像数据中检测一个或多个感兴趣的区域。 使用一组预定义的参数来识别一个或多个淋巴结候选物，该组预定参数对于检测到的每个淋巴结候选者所在的感兴趣区域是特别的。 识别单元可以通过执行DGFR处理来识别一个或多个淋巴结候选。 该方法还可以包括接收用户提供的对所检测到的感兴趣区域特有的预定义参数的调整，并且基于经调整的参数来识别淋巴结候选。 随着提供调整，可以实时地显示基于调整后的参数识别的淋巴结候选以及图像数据。

    Automatic detection of lymph nodes
    3.
    发明授权
    Automatic detection of lymph nodes 有权
    自动检测淋巴结

    公开(公告)号：US08494235B2

    公开(公告)日：2013-07-23

    申请号：US12121865

    申请日：2008-05-16

    申请人： Senthil Periaswamy ,  Xiang Zhou ,  Yiqiang Zhan ,  Arun Krishnan

    发明人： Senthil Periaswamy ,  Xiang Zhou ,  Yiqiang Zhan ,  Arun Krishnan

    IPC分类号： G06K9/00

    CPC分类号： G06T7/0012 ,  G06T7/62 ,  G06T7/68 ,  G06T2207/30101

    摘要： A method for detecting lymph nodes in a medical image includes receiving image data. One or more regions of interest are detected from within the received image data. One or more lymph node candidates are identified using a set of predefined parameters that is particular to the detected region of interest where each lymph node candidate is located. The identifying unit may identify the one or more lymph node candidates by performing DGFR processing. The method may also include receiving user-provided adjustments to the predefined parameters that are particular to the detected regions of interest and identifying the lymph node candidates based on the adjusted parameters. The lymph node candidates identified based on the adjusted parameters may be displayed along with the image data in real-time as the adjustments are provided.

    摘要翻译： 用于检测医学图像中的淋巴结的方法包括接收图像数据。 从所接收的图像数据中检测一个或多个感兴趣的区域。 使用一组预定义的参数来识别一个或多个淋巴结候选物，该组预定参数对于检测到的每个淋巴结候选者所在的感兴趣区域是特别的。 识别单元可以通过执行DGFR处理来识别一个或多个淋巴结候选。 该方法还可以包括接收用户提供的对所检测到的感兴趣区域特有的预定义参数的调整，并且基于经调整的参数来识别淋巴结候选。 随着提供调整，可以实时地显示基于调整后的参数识别的淋巴结候选以及图像数据。

    Registration of Medical Images Using Learned-Based Matching Functions
    4.
    发明申请
    Registration of Medical Images Using Learned-Based Matching Functions 有权
    使用基于学习的匹配功能注册医学图像

    公开(公告)号：US20080267483A1

    公开(公告)日：2008-10-30

    申请号：US12110643

    申请日：2008-04-28

    申请人： Yiqiang Zhan ,  Xiang Zhou ,  Arun Krishnan

    发明人： Yiqiang Zhan ,  Xiang Zhou ,  Arun Krishnan

    IPC分类号： G06K9/00

    CPC分类号： G06K9/32 ,  G06K2209/05 ,  G06T7/33

    摘要： A method for registering a medical image includes acquiring a first medical image of a subject. One or more simulated medical images are synthesized based on the acquired first medical image. One or more matching functions are trained using the first medical image and the simulated medical images. A second medical image of the subject is acquired. The first medical image and the second medical image are registered using the one or more trained matching functions.

    摘要翻译： 用于登记医学图像的方法包括获取对象的第一医学图像。 基于获取的第一医学图像合成一个或多个模拟医学图像。 使用第一医学图像和模拟医学图像训练一个或多个匹配函数。 获取受试者的第二个医学图像。 第一医用图像和第二医用图像使用一个或多个经过训练的匹配功能进行登记。

    Systems and methods for automatic robust anatomy detection through local voting and prediction
    5.
    发明授权
    Systems and methods for automatic robust anatomy detection through local voting and prediction 有权
    通过局部投票和预测自动强化解剖检测的系统和方法

    公开(公告)号：US08160341B2

    公开(公告)日：2012-04-17

    申请号：US12334898

    申请日：2008-12-15

    申请人： Zhigang Peng ,  Yiqiang Zhan ,  Xiang Zhou ,  Arun Krishnan

    发明人： Zhigang Peng ,  Yiqiang Zhan ,  Xiang Zhou ,  Arun Krishnan

    IPC分类号： G06K9/00

    CPC分类号： A61B6/032 ,  A61B6/469 ,  A61B6/488 ,  G06K9/3233 ,  G06K2209/05 ,  G06T7/11 ,  G06T7/73 ,  G06T2207/10081 ,  G06T2207/30048

    摘要： A method for performing a medical imaging study includes acquiring a preliminary scan. A set of local feature candidates is automatically detected from the preliminary scan. The accuracy of each local feature candidate is assessed using multiple combinations of the other local feature candidates and removing a local feature candidate that is assessed to have the lowest accuracy. The assessing and removing steps are repeated until only a predetermined number of local feature candidates remain. A region of interest (ROI) is located from within the preliminary scan based on the remaining predetermined number of local feature candidates. A medical imaging study is performed based on the location of the ROI within the preliminary scan.

    摘要翻译： 执行医学成像研究的方法包括获取初步扫描。 从初步扫描中自动检测一组本地特征候选。 使用其他本地特征候选者的多个组合来评估每个本地特征候选者的准确性，并且去除被评估为具有最低精度的局部特征候选。 重复评估和去除步骤，直到仅保留预定数量的局部特征候选。 感兴趣区域（ROI）基于剩余的预定数量的局部特征候选位于初步扫描内。 基于初步扫描中ROI的位置执行医学成像研究。

    Registration of medical images using learned-based matching functions
    6.
    发明授权
    Registration of medical images using learned-based matching functions 有权
    使用基于学习的匹配功能注册医学图像

    公开(公告)号：US08121362B2

    公开(公告)日：2012-02-21

    申请号：US12110643

    申请日：2008-04-28

    申请人： Yiqiang Zhan ,  Xiang Zhou ,  Arun Krishnan

    发明人： Yiqiang Zhan ,  Xiang Zhou ,  Arun Krishnan

    IPC分类号： G06K9/00

    CPC分类号： G06K9/32 ,  G06K2209/05 ,  G06T7/33

    摘要： A method for registering a medical image includes acquiring a first medical image of a subject. One or more simulated medical images are synthesized based on the acquired first medical image. One or more matching functions are trained using the first medical image and the simulated medical images. A second medical image of the subject is acquired. The first medical image and the second medical image are registered using the one or more trained matching functions.

    摘要翻译： 用于登记医学图像的方法包括获取对象的第一医学图像。 基于获取的第一医学图像合成一个或多个模拟医学图像。 使用第一医学图像和模拟医学图像训练一个或多个匹配函数。 获取受试者的第二个医学图像。 第一医用图像和第二医用图像使用一个或多个经过训练的匹配功能进行登记。

    Systems and Methods for Robust Learning Based Annotation of Medical Radiographs
    7.
    发明申请
    Systems and Methods for Robust Learning Based Annotation of Medical Radiographs 有权
    用于健康学习的系统和方法基于医学影像学的注释

    公开(公告)号：US20100284590A1

    公开(公告)日：2010-11-11

    申请号：US12787916

    申请日：2010-05-26

    申请人： Zhigang Peng ,  Yimo Tao ,  Xiang Sean Zhou ,  Yiqiang Zhan ,  Arun Krishnan

    发明人： Zhigang Peng ,  Yimo Tao ,  Xiang Sean Zhou ,  Yiqiang Zhan ,  Arun Krishnan

    IPC分类号： G06K9/46 ,  G06K9/00

    CPC分类号： A61B6/032 ,  A61B6/469 ,  A61B6/488 ,  G06K9/3233 ,  G06K9/6231 ,  G06K9/6267 ,  G06K2209/05 ,  G06T7/12 ,  G06T7/73 ,  G06T2207/10081 ,  G06T2207/20104 ,  G06T2207/20164 ,  G06T2207/30048

    摘要： Systems and methods for performing a medical imaging study include acquiring a preliminary scan. A set of local feature candidates is automatically detected from the preliminary scan. The accuracy of each local feature candidate is assessed using multiple combinations of the other local feature candidates and removing a local feature candidate that is assessed to have the lowest accuracy. The assessing and removing steps are repeated until only a predetermined number of local feature candidates remain. A region of interest (ROI) is located from within the preliminary scan based on the remaining predetermined number of local feature candidates. A medical imaging study is performed based on the location of the ROI within the preliminary scan.

    摘要翻译： 用于执行医学成像研究的系统和方法包括获取初步扫描。 从初步扫描中自动检测一组本地特征候选。 使用其他本地特征候选者的多个组合来评估每个本地特征候选者的准确性，并且去除被评估为具有最低精度的局部特征候选。 重复评估和去除步骤，直到仅保留预定数量的局部特征候选。 感兴趣区域（ROI）基于剩余的预定数量的局部特征候选位于初步扫描内。 基于初步扫描中ROI的位置执行医学成像研究。

    Systems and methods for robust learning based annotation of medical radiographs
    8.
    发明授权
    Systems and methods for robust learning based annotation of medical radiographs 有权
    用于健康学习的医学放射照片注释的系统和方法

    公开(公告)号：US08369593B2

    公开(公告)日：2013-02-05

    申请号：US12787916

    申请日：2010-05-26

    申请人： Zhigang Peng ,  Yimo Tao ,  Xiang Sean Zhou ,  Yiqiang Zhan ,  Arun Krishnan

    发明人： Zhigang Peng ,  Yimo Tao ,  Xiang Sean Zhou ,  Yiqiang Zhan ,  Arun Krishnan

    IPC分类号： G06K9/00 ,  A61B6/00

    CPC分类号： A61B6/032 ,  A61B6/469 ,  A61B6/488 ,  G06K9/3233 ,  G06K9/6231 ,  G06K9/6267 ,  G06K2209/05 ,  G06T7/12 ,  G06T7/73 ,  G06T2207/10081 ,  G06T2207/20104 ,  G06T2207/20164 ,  G06T2207/30048

    摘要： Systems and methods for performing a medical imaging study include acquiring a preliminary scan. A set of local feature candidates is automatically detected from the preliminary scan. The accuracy of each local feature candidate is assessed using multiple combinations of the other local feature candidates and removing a local feature candidate that is assessed to have the lowest accuracy. The assessing and removing steps are repeated until only a predetermined number of local feature candidates remain. A region of interest (ROI) is located from within the preliminary scan based on the remaining predetermined number of local feature candidates. A medical imaging study is performed based on the location of the ROI within the preliminary scan.

    摘要翻译： 用于执行医学成像研究的系统和方法包括获取初步扫描。 从初步扫描中自动检测一组本地特征候选。 使用其他本地特征候选者的多个组合来评估每个本地特征候选者的准确性，并且去除被评估为具有最低精度的局部特征候选。 重复评估和去除步骤，直到仅保留预定数量的局部特征候选。 感兴趣区域（ROI）基于剩余的预定数量的局部特征候选位于初步扫描内。 基于初步扫描中ROI的位置执行医学成像研究。

    System and method for detection of breast masses and calcifications using the tomosynthesis projection and reconstructed images
    10.
    发明授权
    System and method for detection of breast masses and calcifications using the tomosynthesis projection and reconstructed images 有权
    使用断层合成投影和重建图像检测乳房肿块和钙化的系统和方法

    公开(公告)号：US07840046B2

    公开(公告)日：2010-11-23

    申请号：US11767707

    申请日：2007-06-25

    申请人： Anna Jerebko ,  Arun Krishnan ,  Xiang Zhou

    发明人： Anna Jerebko ,  Arun Krishnan ,  Xiang Zhou

    IPC分类号： G06K9/00 ,  A61B6/04 ,  A61B5/05

    CPC分类号： A61B6/466 ,  A61B6/03 ,  A61B6/502 ,  G06T7/0012 ,  G06T7/97 ,  G06T11/005 ,  G06T2207/10112 ,  G06T2207/10116 ,  G06T2207/30068 ,  G06T2211/436

    摘要： A method of detecting breast masses and calcifications in digitized images, includes providing a plurality of 2-dimensional (2D) digital X-ray projectional breast images acquired from different viewing angles, extracting candidate lesions and 2D features from said 2D projectional images, computing spicularity characteristics of said candidate lesions, including location, periodicity, and amplitude, applying learning algorithms to said candidate lesions to predict a probability of malignancy of said lesion, receiving from said learning algorithm a probability map of detections for each breast image, said detections comprising associating pixels with a probability of being associated with a malignancy, creating a synthetic 2D slice for each X-ray image wherein malignant regions are indicated by ellipses on a non-malignant background, and constructing a synthetic 3-dimensional (3D) image volume from said 2D synthetic slices.

    摘要翻译： 一种在数字化图像中检测乳房肿块和钙化的方法，包括提供从不同视角获取的多个二维（2D）数字X射线投射乳房图像，从所述2D投影图像中提取候选病变和2D特征，计算孢子 所述候选病变的特征，包括位置，周期和幅度，将学习算法应用于所述候选病变以预测所述病变的恶性的概率，从所述学习算法接收每个乳腺图像的检测的概率图，所述检测包括关联 具有与恶性肿瘤相关联的概率的像素，为每个X射线图像创建合成2D切片，其中恶性区域由非恶性背景上的椭圆表示，以及从所述非恶性背景构建合成的三维（3D）图像体积 2D合成切片。