Automatic Detection of Lymph Nodes
    1.
    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

    IPC分类号: G06K9/80

    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
    2.
    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

    IPC分类号: G06K9/00

    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。

    Robust Anatomy Detection Through Local Voting And Prediction
    3.
    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

    IPC分类号: G06K9/00

    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
    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

    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

    IPC分类号: G06K9/00

    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

    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。

    Information-Theoretic View of the Scheduling Problem in Whole-Body Computer Aided Detection/Diagnosis (CAD)
    7.
    发明申请
    Information-Theoretic View of the Scheduling Problem in Whole-Body Computer Aided Detection/Diagnosis (CAD) 有权
    全身计算机辅助检测/诊断(CAD)中调度问题的信息理论观点

    公开(公告)号:US20090037919A1

    公开(公告)日:2009-02-05

    申请号:US12181375

    申请日:2008-07-29

    IPC分类号: G06F9/46

    摘要: A method for automatically scheduling tasks in whole-body computer aided detection/diagnosis (CAD), including: (a) receiving a plurality of tasks to be executed by a whole-body CAD system; (b) identifying a task to be executed, wherein the task to be executed has an expected information gain that is greater than that of each of the other tasks; (c) executing the task with the greatest expected information gain and removing the executed task from further analysis; and (d) repeating steps (b) and (c) for the remaining tasks.

    摘要翻译: 一种全身计算机辅助检测/诊断(CAD)中自动调度任务的方法,包括:(a)接收由全身CAD系统执行的多个任务; (b)识别要执行的任务,其中待执行的任务具有大于其他任务中的每一个的预期信息增益; (c)以最大的预期信息获取执行任务,并将执行的任务从进一步分析中移除; 和(d)对剩余的任务重复步骤(b)和(c)。

    Information-theoretic view of the scheduling problem in whole-body computer aided detection/diagnosis (CAD)
    8.
    发明授权
    Information-theoretic view of the scheduling problem in whole-body computer aided detection/diagnosis (CAD) 有权
    全身计算机辅助检测/诊断(CAD)调度问题的信息理论观点

    公开(公告)号:US09135401B2

    公开(公告)日:2015-09-15

    申请号:US12181375

    申请日:2008-07-29

    IPC分类号: G06F19/00

    摘要: A method for automatically scheduling tasks in whole-body computer aided detection/diagnosis (CAD), including: (a) receiving a plurality of tasks to be executed by a whole-body CAD system; (b) identifying a task to be executed, wherein the task to be executed has an expected information gain that is greater than that of each of the other tasks; (c) executing the task with the greatest expected information gain and removing the executed task from further analysis; and (d) repeating steps (b) and (c) for the remaining tasks.

    摘要翻译: 一种全身计算机辅助检测/诊断(CAD)中自动调度任务的方法,包括:(a)接收由全身CAD系统执行的多个任务; (b)识别要执行的任务,其中待执行的任务具有大于其他任务中的每一个的预期信息增益; (c)以最大的预期信息获取执行任务,并将执行的任务从进一步分析中移除; 和(d)对剩余的任务重复步骤(b)和(c)。

    Joint Detection and Localization of Multiple Anatomical Landmarks Through Learning
    9.
    发明申请
    Joint Detection and Localization of Multiple Anatomical Landmarks Through Learning 有权
    通过学习联合检测和定位多个解剖标志

    公开(公告)号:US20090034813A1

    公开(公告)日:2009-02-05

    申请号:US12180674

    申请日:2008-07-28

    IPC分类号: G06K9/00

    摘要: A method for detecting and localizing multiple anatomical landmarks in medical images including: receiving an input requesting identification of a plurality of anatomical landmarks in a medical image; applying a multi-landmark detector to the medical image to identify a plurality of candidate locations for each of the anatomical landmarks; for each of the anatomical landmarks, applying a landmark-specific detector to each of its candidate locations, wherein the landmark-specific detector assigns a score to each of the candidate locations, and wherein candidate locations having a score below a predetermined threshold are removed; applying spatial statistics to groups of the remaining candidate locations to determine, for each of the anatomical landmarks, the candidate location that most accurately identifies the anatomical landmark; and for each of the anatomical landmarks, outputting the candidate location that most accurately identifies the anatomical landmark.

    摘要翻译: 一种用于检测和定位医学图像中的多个解剖标志的方法,包括:接收请求在医学图像中识别多个解剖标志的输入; 将多标记检测器应用于医学图像以识别每个解剖标志的多个候选位置; 对于每个解剖标志,对其每个候选位置应用地标特异性检测器,其中所述地标专用检测器为每个所述候选位置分配得分,并且其中具有低于预定阈值的得分的候选位置被去除; 将空间统计学应用于剩余候选位置的组,以针对每个解剖学标记确定最准确地识别解剖学标记的候选位置; 并且对于每个解剖标志,输出最准确地识别解剖标志的候选位置。

    Joint detection and localization of multiple anatomical landmarks through learning
    10.
    发明授权
    Joint detection and localization of multiple anatomical landmarks through learning 有权
    通过学习联合检测和定位多个解剖标志

    公开(公告)号:US08160322B2

    公开(公告)日:2012-04-17

    申请号:US12180674

    申请日:2008-07-28

    IPC分类号: G06K9/00

    摘要: A method for detecting and localizing multiple anatomical landmarks in medical images, including: receiving an input requesting identification of a plurality of anatomical landmarks in a medical image; applying a multi-landmark detector to the medical image to identify a plurality of candidate locations for each of the anatomical landmarks; for each of the anatomical landmarks, applying a landmark-specific detector to each of its candidate locations, wherein the landmark-specific detector assigns a score to each of the candidate locations, and wherein candidate locations having a score below a predetermined threshold are removed; applying spatial statistics to groups of the remaining candidate locations to determine, for each of the anatomical landmarks, the candidate location that most accurately identifies the anatomical landmark; and for each of the anatomical landmarks, outputting the candidate location that most accurately identifies the anatomical landmark.

    摘要翻译: 一种用于检测和定位医学图像中的多个解剖标志的方法,包括:接收请求在医学图像中识别多个解剖标志的输入; 将多标记检测器应用于医学图像以识别每个解剖标志的多个候选位置; 对于每个解剖标志,对其每个候选位置应用地标特异性检测器,其中所述地标专用检测器为每个所述候选位置分配得分,并且其中具有低于预定阈值的得分的候选位置被去除; 将空间统计学应用于剩余候选位置的组,以针对每个解剖学标记确定最准确地识别解剖学标记的候选位置; 并且对于每个解剖标志,输出最准确地识别解剖标志的候选位置。