OPTIMAL SCHEDULING FOR CAD ARCHITECTURE
    1.
    发明申请
    OPTIMAL SCHEDULING FOR CAD ARCHITECTURE 审中-公开
    CAD架构的最佳调度

    公开(公告)号:US20090165009A1

    公开(公告)日:2009-06-25

    申请号:US12335344

    申请日:2008-12-15

    IPC分类号: G06F9/46

    CPC分类号: G06F9/4881 G06F19/321

    摘要: A system and method for optimal scheduling of image processing jobs is provided. Requests for processing originate either from a DICOM service that receives images sent to the system, and forwards those for batch processing, or from an interactive workstation application, which requests interactive CAD processing. Each request is placed onto a queue which is sorted first by priority, and second by the time that the request is added to the queue. Requests for interactive processing from a workstation application are added to the queue with the highest priority, whereas requests for batch processing are added at a low priority. The algorithm service takes the top-most item from the queue and passes the request to the algorithms which it hosts, and when that processing is completed, it sends a message to one or more output queues.

    摘要翻译: 提供了用于图像处理作业的最优调度的系统和方法。 处理请求源自接收发送到系统的映像的DICOM服务,并转发用于批处理的映像,或者从请求交互式CAD处理的交互式工作站应用程序转发。 每个请求被放置到首先按优先级排序的队列,第二个队列被添加到队列中。 从工作站应用程序进行交互处理的请求将被添加到具有最高优先级的队列中,而对批处理的请求以低优先级被添加。 算法服务从队列中获取最多的项目,并将请求传递给其所承载的算法,当该处理完成时,它将向一个或多个输出队列发送消息。

    ALGORITHMS FOR SELECTING MASS DENSITY CANDIDATES FROM DIGITAL MAMMOGRAMS
    2.
    发明申请
    ALGORITHMS FOR SELECTING MASS DENSITY CANDIDATES FROM DIGITAL MAMMOGRAMS 有权
    从数字农场选择质量密度考虑的算法

    公开(公告)号:US20080267470A1

    公开(公告)日:2008-10-30

    申请号:US12099785

    申请日:2008-04-09

    IPC分类号: G06K9/00

    摘要: The present invention provides a method for selecting mass density candidates from mammograms for computer-aided lesion detection, review and diagnosis. The method has two steps: a Gaussian difference filter to enhance the intensity and a Canny detector to find potential mass density contours. For circumscribed masses, an additional Hough circle detector is used. This invention makes use of both intensity and morphology information and only processes each image at a single gray-level, so both sensitivity and processing time are improved. The selection algorithm can be also used to select mass candidates from ultrasound images, from 3D tomosynthesis mammography images and from breast MRI images.

    摘要翻译: 本发明提供了一种用于从计算机辅助病变检测,检查和诊断的乳房X线照片中选择质量密度候选的方法。 该方法有两个步骤:一个增强强度的高斯差分滤波器和一个Canny探测器,找出潜在的质量密度轮廓。 对于外接质量,使用另外的霍夫圆检测器。 本发明利用强度和形态信息,并且仅在单个灰度级处理每个图像,因此提高了灵敏度和处理时间。 选择算法还可用于从超声图像,3D断层合成乳房X线照相图像和乳房MRI图像中选择质量候选。

    Fast preprocessing algorithms for digital mammography CAD and workstation
    3.
    发明授权
    Fast preprocessing algorithms for digital mammography CAD and workstation 有权
    数字乳腺X线照相CAD和工作站的快速预处理算法

    公开(公告)号:US08340387B2

    公开(公告)日:2012-12-25

    申请号:US12053609

    申请日:2008-03-23

    IPC分类号: G06K9/00 A61B6/04

    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
    4.
    发明授权
    Combination machine learning algorithms for computer-aided detection, review and diagnosis 有权
    用于计算机辅助检测,检查和诊断的组合机器学习算法

    公开(公告)号:US08296247B2

    公开(公告)日:2012-10-23

    申请号:US12053600

    申请日:2008-03-22

    摘要: A method of reviewing medical images and clinical data to generate a diagnosis or treatment decision is provided. The method includes receiving, at a computer-aided detection (CAD) system, the medical images and clinical data, processing the medical images and clinical data; to generate initial finding candidates and clustering the initial finding candidates into a plurality of groups. The method further includes classifying the initial finding candidates using machine learning algorithms integrated into the CAD system into one or more categories one or more categories of the initial finding candidates using type 2 fuzz logic, and determining detection and assessment statistics based on at least the assessed categories and classified findings using Bayesian probability analysis. The method also includes modifying the classified findings and assessed categories based on additional interactive input, and generating the diagnosis or treatment decision based on the determined detection, assessment statistics, and the additional interactive input.

    摘要翻译: 提供了一种检查医学图像和临床数据以产生诊断或治疗决定的方法。 该方法包括在计算机辅助检测(CAD)系统中接收医学图像和临床数据,处理医学图像和临床数据; 以产生初始发现候选者并将初始发现候选者聚类成多个组。 该方法还包括使用集成到CAD系统中的机器学习算法将初始发现候选分类为使用类型2模糊逻辑的一个或多个类别的初始发现候选者的一个或多个类别,以及至少基于所评估的确定的检测和评估统计 使用贝叶斯概率分析的类别和分类发现。 该方法还包括基于额外的交互输入修改分类发现和评估类别,以及基于所确定的检测,评估统计和附加交互输入来生成诊断或治疗决定。

    IMAGE NORMALIZATION FOR COMPUTER-AIDED DETECTION, REVIEW AND DIAGNOSIS
    5.
    发明申请
    IMAGE NORMALIZATION FOR COMPUTER-AIDED DETECTION, REVIEW AND DIAGNOSIS 审中-公开
    计算机辅助检测,检查和诊断的图像正常化

    公开(公告)号:US20090238421A1

    公开(公告)日:2009-09-24

    申请号:US12050911

    申请日:2008-03-18

    IPC分类号: G06K9/00

    摘要: A method and apparatus for processing medical images from one of a plurality of digital acquisition modalities or manufacturers with different imaging condition is proposed for creating consistent appearance of the images. The method comprises (1) tissue segmentation to isolate the region of interest; (2) dynamic extraction of the optimal parameters for image transformation from the segmented region; (3) generation of a transformation function from the individual image optimized parameters; and (4) use of the transformation function to produce images that have consistent image characteristics. This method also applies to multiple images from a single study or multiple studies. The transformed images can be used for computer-aided lesion detection, review and diagnosis.

    摘要翻译: 提出了一种用于从具有不同成像条件的多个数字采集模式或制造商之一处理医学图像的方法和装置,用于创建图像的一致外观。 该方法包括(1)组织分割以分离感兴趣的区域; (2)动态提取分割区域图像变换的最优参数; (3)从各个图像优化参数生成变换函数; 和(4)使用变换函数来产生具有一致图像特征的图像。 这种方法也适用于单一研究或多项研究的多个图像。 转换的图像可用于计算机辅助病变检测,检查和诊断。

    Mass spicules detection and tracing from digital mammograms
    6.
    发明授权
    Mass spicules detection and tracing from digital mammograms 有权
    从数字乳腺X线照片检测和追踪大量针刺

    公开(公告)号:US08208700B2

    公开(公告)日:2012-06-26

    申请号:US12119295

    申请日:2008-05-12

    IPC分类号: G06K9/00 G06K9/34 A61B6/04

    摘要: The present invention provides an algorithm to detect and trace the spicules of a mass density in digital mammograms using an adaptive threshold edge algorithm and a flood-fill segmentation algorithm. Elongation criteria are used to remove false edges that do not radiate from a central mass margin. The algorithm works on a central mass border and spicules feature map that contains a subset of the pixels from the source image, so processing time is fast enough for use in a mammography CAD server and for real-time computation within a digital mammography workstation.

    摘要翻译: 本发明提供一种使用自适应阈值边缘算法和洪水填充分割算法来检测和追踪数字乳房X线照片中的质量密度的尖端的算法。 伸长率标准用于去除不会从中心质量边缘辐射的假边缘。 该算法适用于包含来自源图像的像素子集的中心质量边界和针尖特征图,因此处理时间足够快以用于乳房X射线摄影CAD服务器并在数字乳腺摄影工作站内进行实时计算。

    DUAL-MAGNIFY-GLASS VISUALIZATION FOR SOFT-COPY MAMMOGRAPHY VIEWING
    7.
    发明申请
    DUAL-MAGNIFY-GLASS VISUALIZATION FOR SOFT-COPY MAMMOGRAPHY VIEWING 审中-公开
    软复制浏览的双倍光栅可视化

    公开(公告)号:US20090154782A1

    公开(公告)日:2009-06-18

    申请号:US12334474

    申请日:2008-12-14

    IPC分类号: G06K9/00

    摘要: This invention provides a dual-magnify-glass viewing method for a mammography workstation. In particular, the invention includes a method that registers regions of interest on a pair of mammography images and provides a user interface to visualize the paired full resolution or magnified images in a synchronized style. The paired images are two views that can be either left and right bilateral mammogram views; two alternative projection mammogram views, or corresponding current and prior same mammogram views. The paired images can also be two views from different modalities, such as, X-ray and ultrasound images. This invention can be used to aid the radiologist to more effectively view mammography or other breast images.

    摘要翻译: 本发明提供了一种用于乳房摄影工作站的双倍放大镜观察方法。 特别地,本发明包括一种在一对乳房摄影图像上登记感兴趣区域并提供用户界面以以同步的方式可视化配对的全分辨率或放大图像的方法。 配对的图像是两个视图,可以是左右乳房X线照片视图; 两个替代的投影乳房X线照片视图,或相应的当前和之前相同的乳房X线照片视图。 成对的图像也可以是来自不同形态的两个视图,例如X射线和超声图像。 本发明可以用于帮助放射科医生更有效地观察乳房X线照相术或其他乳房图像。

    MASS SPICULES DETECTION AND TRACING FROM DIGITAL MAMMOGRAMS
    8.
    发明申请
    MASS SPICULES DETECTION AND TRACING FROM DIGITAL MAMMOGRAMS 有权
    大量SPICULES检测和跟踪从数字农业

    公开(公告)号:US20080285825A1

    公开(公告)日:2008-11-20

    申请号:US12119295

    申请日:2008-05-12

    IPC分类号: G06K9/00

    摘要: The present invention provides an algorithm to detect and trace the spicules of a mass density in digital mammograms using an adaptive threshold edge algorithm and a flood-fill segmentation algorithm. Elongation criteria are used to remove false edges that do not radiate from a central mass margin. The algorithm works on a central mass border and spicules feature map that contains a subset of the pixels from the source image, so processing time is fast enough for use in a mammography CAD server and for real-time computation within a digital mammography workstation.

    摘要翻译: 本发明提供一种使用自适应阈值边缘算法和洪水填充分割算法来检测和追踪数字乳房X线照片中的质量密度的尖端的算法。 伸长率标准用于去除不会从中心质量边缘辐射的假边缘。 该算法适用于包含来自源图像的像素子集的中心质量边界和针尖特征图,因此处理时间足够快以用于乳房X射线摄影CAD服务器并在数字乳腺摄影工作站内进行实时计算。

    Computer-aided diagnosis and visualization of tomosynthesis mammography data
    9.
    发明授权
    Computer-aided diagnosis and visualization of tomosynthesis mammography data 有权
    计算机辅助诊断和可视化的断层扫描X线摄影数据

    公开(公告)号:US08184890B2

    公开(公告)日:2012-05-22

    申请号:US12344451

    申请日:2008-12-26

    IPC分类号: G06K9/00

    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。

    Algorithms for selecting mass density candidates from digital mammograms
    10.
    发明授权
    Algorithms for selecting mass density candidates from digital mammograms 有权
    用于从数字乳腺X线照片中选择质量密度候选者的算法

    公开(公告)号:US08086002B2

    公开(公告)日:2011-12-27

    申请号:US12099785

    申请日:2008-04-09

    IPC分类号: G06K9/00

    摘要: The present invention provides a method for selecting mass density candidates from digital image, for example mammograms, for computer-aided lesion detection, review and diagnosis. A method of selecting mass density candidates from a digital image for computer-aided cancer detection, review and diagnosis includes down-sampling the digital image to a low resolution; smoothing an edge along a skinline; applying a Gaussian difference filter to enhance intensity to form a filtered image; masking the filtered image using a breast mask; using a Canny detector to find potential mass density contours; and generating a mass density candidate list from Canny contours produced in the Canny detector.

    摘要翻译: 本发明提供一种用于从数字图像(例如乳房X线照片)中选择质量密度候选的方法,用于计算机辅助病变检测,检查和诊断。 从计算机辅助癌症检测,检查和诊断的数字图像中选择质量密度候选的方法包括将数字图像下采样到低分辨率; 沿着皮肤平滑边缘; 应用高斯差分滤波器来增强强度以形成滤波图像; 使用乳房掩模掩蔽滤波图像; 使用Canny检测器查找潜在的质量密度轮廓; 并从Canny检测器中产生的Canny轮廓生成质量密度候选列表。