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    FAST PREPROCESSING ALGORITHMS FOR DIGITAL MAMMOGRAPHY CAD AND WORKSTATION
    4.
    发明申请
    FAST PREPROCESSING ALGORITHMS FOR DIGITAL MAMMOGRAPHY CAD AND WORKSTATION 有权
    用于数字印刷CAD和工作站的快速预处理算法

    公开(公告)号：US20090220138A1

    公开(公告)日：2009-09-03

    申请号：US12053609

    申请日：2008-03-23

    申请人： Heidi Zhang ,  Patrick Heffernan

    发明人： Heidi Zhang ,  Patrick Heffernan

    IPC分类号： G06K9/00

    CPC分类号： G06T7/12 ,  G06T2207/10116 ,  G06T2207/30068

    摘要： A method and apparatus are disclosed for an image preprocessing device that automatically detects chestwall laterality; removes border artifacts; and segments breast tissue and pectoral muscle from digital mammograms. The algorithms in the preprocessing device utilize the computer cache, a vertical Sobel filter and a probabilistic Hough transform to detect curved edges. The preprocessing result, along with a pseudo-modality normalized image, can be used as input to a CAD (computer-aided detection) server or to a mammography image review workstation. In the case of workstation input, the preprocessing results improve the protocol for chestwall-to-chestwall image hanging, and support optimal image contrast display of each segmented region.

    摘要翻译： 公开了一种图像预处理装置的方法和装置，其自动检测胸壁侧向性; 删除边界人造物; 并从数字乳腺X线照片分割乳腺组织和胸肌。 预处理装置中的算法利用计算机缓存，垂直Sobel滤波器和概率霍夫变换来检测弯曲边缘。 预处理结果以及伪模态归一化图像可以用作CAD（计算机辅助检测）服务器或乳腺X线照相图像检查工作站的输入。 在工作站输入的情况下，预处理结果提高了胸壁至胸壁图像挂起的协议，并支持每个分段区域的最佳图像对比度显示。

    COMBINATION MACHINE LEARNING ALGORITHMS FOR COMPUTER-AIDED DETECTION, REVIEW AND DIAGNOSIS
    5.
    发明申请
    COMBINATION MACHINE LEARNING ALGORITHMS FOR COMPUTER-AIDED DETECTION, REVIEW AND DIAGNOSIS 有权
    用于计算机辅助检测，审查和诊断的组合机器学习算法

    公开(公告)号：US20090171871A1

    公开(公告)日：2009-07-02

    申请号：US12053600

    申请日：2008-03-22

    申请人： Heidi Zhang ,  Patrick Heffernan

    发明人： Heidi Zhang ,  Patrick Heffernan

    IPC分类号： G06F15/18 ,  G06N3/08

    CPC分类号： G06N99/005 ,  G06F19/00 ,  G06N7/005 ,  G16H50/20

    摘要： This invention utilizes a number of Computational Intelligence (CI) techniques with different learning methods in a computer-aided detection, review and diagnosis (CAD) device. Specifically, an unsupervised learning method is used for clustering of types of abnormal findings. Then a number of classifiers for each type of findings are trained with appropriate learning algorithms; and combined in three different manners to produce one classifier that can be operated at three different operating points. A fuzzy system is used for mapping the findings to diagnostic reports constructed using a formal language. Finally, the finding statistics is calculated based on Bayesian probability. During image review, the device provides the readers some insight as to how it derives its outputs. The output of the device can be updated in an interactive and progressive manner by a human reader (radiologist). The output from classification can be updated by the human, and is fed as input to the assessment task. Again the output from assessment can be updated by the human reader, and is fed as input for the machine to produce statistical information. If so configured, the interactive information can be added to an online database so that the device can adapt its future behavior based on the new information.

    摘要翻译： 本发明在计算机辅助检测，检查和诊断（CAD）设备中利用具有不同学习方法的许多计算智能（CI）技术。 具体来说，无监督学习方法用于异常发现类型的聚类。 然后用适当的学习算法训练每种类型发现的一些分类器; 并以三种不同的方式组合，以生产一种可在三个不同操作点操作的分选机。 使用模糊系统将结果映射到使用正式语言构建的诊断报告。 最后，发现统计是基于贝叶斯概率计算的。 在图像审查期间，该设备为读者提供了有关如何获取其输出的一些见解。 人类读者（放射科医生）可以交互式和渐进的方式更新装置的输出。 分类的输出可以由人员更新，并作为输入进行评估任务。 评估结果再次可由人类阅读器进行更新，并作为机器的输入进行输入以产生统计信息。 如果这样配置，则可以将交互式信息添加到在线数据库，使得设备可以基于新信息来适应其未来的行为。

    COMPUTER-AIDED DIAGNOSIS AND VISUALIZATION OF TOMOSYNTHESIS MAMMOGRAPHY DATA
    6.
    发明申请
    COMPUTER-AIDED DIAGNOSIS AND VISUALIZATION OF TOMOSYNTHESIS MAMMOGRAPHY DATA 有权
    计算机辅助诊断和可视化TOMOSYNTHESIS MAMMOGRAPHY数据

    公开(公告)号：US20100166267A1

    公开(公告)日：2010-07-01

    申请号：US12344451

    申请日：2008-12-26

    申请人： Heidi Zhang ,  Patrick Heffernan

    发明人： Heidi Zhang ,  Patrick Heffernan

    IPC分类号： G06K9/00 ,  A61B6/00

    CPC分类号： A61B6/463 ,  A61B6/502 ,  A61B6/5235 ,  G06K2209/053 ,  G06T7/0012 ,  G06T2207/10081 ,  G06T2207/30068 ,  Y10S128/922

    摘要： The present invention provides a method and system using computer-aided detection (CAD) algorithms to aid diagnosis and visualization of tomosynthesis mammography data. The proposed CAD algorithms process two-dimensional and three-dimensional tomosynthesis mammography images and identify regions of interest in breasts. The CAD algorithms include the steps of preprocessing; candidate detection of potential regions of interest; and classification of each region of interest to aid reading by radiologists. The detection of potential regions of interest utilizes two dimensional projection images for generating candidates. The resultant candidates in two dimensional images are back-projected into the three dimensional volume images. The feature extraction for classification operates in the three dimensional image in the neighborhood of the back-projected candidate location. The forward-projection and back-projection algorithms are used for visualization of the tomosynthesis mammography data in a fashion of synchronized MPR and VR.

    摘要翻译： 本发明提供了一种使用计算机辅助检测（CAD）算法来帮助诊断和可视化体层摄影乳腺X线照相术数据的方法和系统。 提出的CAD算法处理二维和三维断层摄影乳腺X线照相图像并识别乳房感兴趣的区域。 CAD算法包括预处理步骤; 候选人检测潜在的感兴趣区域; 并分类每个感兴趣的区域以帮助放射科医师的阅读。 感兴趣的潜在区域的检测利用二维投影图像来产生候选。 将二维图像中的合成候选物反投影到三维体积图像中。 用于分类的特征提取在背投影候选位置附近的三维图像中操作。 前投影和后投影算法用于以同步的MPR和VR的方式可视化断层摄影乳房X线照相术数据。

    COMMUNICATIVE CAD SYSTEM FOR ASSISTING BREAST IMAGING DIAGNOSIS
    10.
    发明申请
    COMMUNICATIVE CAD SYSTEM FOR ASSISTING BREAST IMAGING DIAGNOSIS 审中-公开
    用于辅助乳腺成像诊断的通信CAD系统

    公开(公告)号：US20090238422A1

    公开(公告)日：2009-09-24

    申请号：US12120084

    申请日：2008-05-13

    申请人： Heidi Zhang ,  Patrick Heffernan

    发明人： Heidi Zhang ,  Patrick Heffernan

    IPC分类号： G06K9/00

    CPC分类号： G06Q10/00 ,  A61B6/502 ,  A61B6/563 ,  A61B8/0825 ,  A61B8/565

    摘要： This invention provides a computational intelligence method and system that can be used interactively by a radiologist in a “concurrent read” model to aid diagnosis from medical images. In particular, the invention operates more like a very patient, indefatigable knowledge accumulating and communicating companion for the radiologist, rather than a second “expert” whose advice is sought after a normal review. The system works interactively with the radiologist during image reading, prompting areas to review in more detail, providing computer generated features and interpretation, and suggesting potential diagnoses for areas of suspicion that are identified either by the machine or the human. In addition, the human can obtain more information from the system—the radiologist can query as to why a particular region is highlighted, or why a particular diagnosis is postulated for an area. Conversely, the system learns from the human—the radiologist identifies areas that should be marked, and updates the computer's knowledge of what the diagnosis should be for that area.

    摘要翻译： 本发明提供了一种计算智能方法和系统，其可以由“同时读取”模型中的放射科医生交互地使用，以辅助医学图像的诊断。 特别地，本发明更像是放射科医师的非常耐心，不知疲倦的知识积累和沟通的伴侣，而不是在通常的检查之后寻求其建议的第二个“专家”。 该系统在图像阅读期间与放射科医生进行交互工作，提示区域进行更详细的审查，提供计算机生成的特征和解释，并提出可能由机器或人类识别的怀疑区域的诊断。 此外，人类可以从系统获取更多信息 - 放射科医生可以查询特定区域为何突出显示，或为什么假定某个区域的特定诊断。 相反，系统从人类学习 - 放射科医生识别应标记的区域，并更新计算机对该区域的诊断应具备的知识。