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    Method and system for performing patient specific analysis of disease relevant changes of a disease in an anatomical structure
    2.
    发明申请
    Method and system for performing patient specific analysis of disease relevant changes of a disease in an anatomical structure 有权
    方法和系统，用于对解剖学结构中疾病的疾病相关变化进行患者特异性分析

    公开(公告)号：US20070053560A1

    公开(公告)日：2007-03-08

    申请号：US11220782

    申请日：2005-09-07

    申请人： James Miller ,  Paulo Ricardo Mendonca

    发明人： James Miller ,  Paulo Ricardo Mendonca

    IPC分类号： G06K9/00

    CPC分类号： G06T7/0012

    摘要： A method for performing patient specific analysis of disease relevant changes of a disease in an anatomical structure of interest is provided. The method comprises determining a percentage of the anatomical structure that is encompassed by a diseased tissue region using a patient specific healthy tissue model. The method then comprises determining the amount or spatial distribution or a combination thereof of tissue volume variation due to the disease in the anatomical structure based on the percentage of the anatomical structure encompassed by the diseased tissue region and an estimated original amount of tissue.

    摘要翻译： 提供了一种在感兴趣的解剖结构中进行疾病相关疾病变化的患者特异性分析的方法。 该方法包括使用患者特定的健康组织模型确定由患病组织区域包围的解剖结构的百分比。 该方法然后包括基于由病变组织区域包围的解剖结构的百分比和估计的原始组织量来确定由于解剖结构中的疾病引起的组织体积变化的量或空间分布或其组合。

    Method and system for measuring disease relevant tissue changes
    5.
    发明授权
    Method and system for measuring disease relevant tissue changes 有权
    测量疾病相关组织变化的方法和系统

    公开(公告)号：US07283652B2

    公开(公告)日：2007-10-16

    申请号：US10065894

    申请日：2002-11-27

    申请人： Paulo Ricardo Mendonca ,  Matthew William Turek ,  James Vradenburg Miller ,  Robert August Kaucic ,  Peter Henry Tu ,  Tony Chishao Pan

    发明人： Paulo Ricardo Mendonca ,  Matthew William Turek ,  James Vradenburg Miller ,  Robert August Kaucic ,  Peter Henry Tu ,  Tony Chishao Pan

    IPC分类号： G06K9/00

    CPC分类号： G06T7/0012 ,  G06T2207/30061

    摘要： A method and system for measuring disease relevant tissue changes for use in quantifying, diagnosing and predicting a given disease are provided. The method comprises applying at least one segmenting process to the image data to generate a plurality of segmented regions of interest, extracting features relevant for a given disease from the segmented regions to generate extracted features, and mathematically modeling the features for use in one of diagnosing, quantifying and predicting changes indicative of the given disease. The system comprises an imaging device for acquiring the image data and an image process configured to segment, extract and mathematically model disease relevant features.

    摘要翻译： 提供了用于量化，诊断和预测给定疾病的用于测量疾病相关组织变化的方法和系统。 该方法包括对图像数据应用至少一个分割过程以产生多个感兴趣的分割区域，从分割区域提取与给定疾病相关的特征以产生提取的特征，以及数学模拟特征以用于诊断之一 ，量化和预测指示给定疾病的变化。 该系统包括用于获取图像数据的成像装置和被配置为分割，提取和数学地模拟疾病相关特征的图像处理。

    Sequential approach for automatic defect recognition
    7.
    发明授权
    Sequential approach for automatic defect recognition 有权
    自动缺陷识别的顺序方法

    公开(公告)号：US08345949B2

    公开(公告)日：2013-01-01

    申请号：US12720234

    申请日：2010-03-09

    申请人： Fei Zhao ,  Robert August Kaucic ,  Paulo Ricardo Mendonca

    发明人： Fei Zhao ,  Robert August Kaucic ,  Paulo Ricardo Mendonca

    IPC分类号： G06K9/00

    CPC分类号： G06T7/0004 ,  G06T2207/10081 ,  G06T2207/20012 ,  G06T2207/20016 ,  G06T2207/30116 ,  G06T2207/30164

    摘要： A method of automatic defect recognition includes receiving a initial set of inspection image data of a scanned object from a scanning machine; applying a first image analysis algorithm to this set of inspection image data; then removing from the set of inspection image data any defect-free image regions, so as to retain a set of analyzed inspection image data; applying an additional image analysis algorithm(s) to the set of analyzed inspection image data, wherein the additional algorithm(s) has a higher computational cost than the first image analysis algorithm; and based on the applying of the additional image analysis algorithm(s), removing from the first set of inspection image data a second set of defect-free image regions, thereby retaining a set of twice-analyzed inspection image data.

    摘要翻译： 一种自动缺陷识别方法包括从扫描机接收扫描物体的初始检查图像数据集; 对该组检查图像数据应用第一图像分析算法; 然后从所述一组检查图像数据中去除任何无缺陷的图像区域，以便保留一组分析的检查图像数据; 对所分析的检查图像数据集合应用附加图像分析算法，其中所述附加算法具有比所述第一图像分析算法更高的计算成本; 并且基于附加图像分析算法的应用，从第一组检查图像数据中移除第二组无缺陷图像区域，从而保留一组两次分析的检查图像数据。

    Method and system for identifying defects in radiographic image data corresponding to a scanned object
    8.
    发明授权
    Method and system for identifying defects in radiographic image data corresponding to a scanned object 有权
    用于识别与扫描对象相对应的放射线图像数据中的缺陷的方法和系统

    公开(公告)号：US08238635B2

    公开(公告)日：2012-08-07

    申请号：US12052943

    申请日：2008-03-21

    申请人： Ali Can ,  Robert August Kaucic ,  Paulo Ricardo Mendonca ,  Zhaohui Sun ,  Joseph Manuel Portaz

    发明人： Ali Can ,  Robert August Kaucic ,  Paulo Ricardo Mendonca ,  Zhaohui Sun ,  Joseph Manuel Portaz

    IPC分类号： G06K9/00

    CPC分类号： G06T7/001 ,  G06T2207/10116 ,  G06T2207/30004

    摘要： A method for identifying defects in radiographic image data corresponding to a scanned object is provided. The method includes acquiring radiographic image data corresponding to a scanned object. In one embodiment, the radiographic image data includes an inspection test image and a reference image corresponding to the scanned object. The method includes identifying one or more regions of interest in the reference image and aligning the inspection test image with the regions of interest identified in the reference image, to obtain a residual image. The method further includes identifying one or more defects in the inspection test image based upon the residual image and one or more defect probability values computed for one or more pixels in the residual image.

    摘要翻译： 提供了一种用于识别与扫描对象相对应的放射线图像数据中的缺陷的方法。 该方法包括获取与扫描对象相对应的放射线图像数据。 在一个实施例中，放射照相图像数据包括检查测试图像和对应于被扫描物体的参考图像。 该方法包括识别参考图像中的一个或多个感兴趣区域并使检查测试图像与参考图像中标识的感兴趣区域对准，以获得残差图像。 该方法还包括基于对残差图像中的一个或多个像素计算的残差图像和一个或多个缺陷概率值来识别检查测试图像中的一个或多个缺陷。