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    Method and system for automated detection of clustered microcalcifications from digital mammograms
    2.
    发明授权
    Method and system for automated detection of clustered microcalcifications from digital mammograms 失效
    用于检测数字乳腺X线照片中聚集微钙化的最佳参数选择

    公开(公告)号：US06205236B1

    公开(公告)日：2001-03-20

    申请号：US09416437

    申请日：1999-10-12

    申请人： Steven K. Rogers ,  Philip Amburn ,  Telford S. Berkey ,  Randy P. Broussard ,  Martin P. DeSimio ,  Jeffrey W. Hoffmeister ,  Edward M. Ochoa ,  Thomas F. Rathbun ,  John E. Rosenstengel

    发明人： Steven K. Rogers ,  Philip Amburn ,  Telford S. Berkey ,  Randy P. Broussard ,  Martin P. DeSimio ,  Jeffrey W. Hoffmeister ,  Edward M. Ochoa ,  Thomas F. Rathbun ,  John E. Rosenstengel

    IPC分类号： G06K900

    CPC分类号： B25J15/04 ,  A61B6/502 ,  B29C49/0021 ,  B29C2791/006 ,  B29C2791/007 ,  B29L2023/18 ,  G06K9/38 ,  G06K9/4609 ,  G06K9/6254 ,  G06K2209/05 ,  G06T5/20 ,  G06T7/0012 ,  Y10S128/922

    摘要： A method and system for detecting and displaying clustered microcalcifications in a digital mammogram, wherein a single digital mammogram is first automatically cropped to a breast area sub-image which is then processed by means of an optimized Difference of Gaussians filter to enhance the appearance of potential microcalcifications in the sub-image. The potential microcalcifications are thresholded clusters are detected, features are computed for the detected clusters, and the clusters are classified as either suspicious or not suspicious by means of a neural network. Thresholding is preferably by sloping local thresholding but may also be performed by global and dual-local thresholding. The locations in the original digital mammogram of the suspicious detected clustered microcalcifications are indicated. Parameters for use in the detection and thresholding portions of the system are computer-optimized by means of a genetic algorithm. The results of the system are optimally combined with a radiologist's observation of the original mammogram by combining the observations with the results, after the radiologist has first accepted or rejected individual detections reported by the system.

    摘要翻译： 一种用于在数字乳腺X线照片中检测和显示聚类微钙化的方法和系统，其中首先将单个数字乳腺X线照片自动裁剪到乳房区域子图像，然后通过优化的高斯差分滤波器处理以增强潜在的外观 子图像中的微钙化。 潜在的微钙化是被检测到的阈值聚类，针对检测到的聚类计算特征，并且通过神经网络将聚类分类为可疑的或不可疑的。 阈值优选地通过倾斜的局部阈值来进行，但是也可以通过全局和双局部阈值来执行。 指出了可疑检测到的聚集微量钙化的原始数字乳腺X线照片中的位置。 用于系统的检测和阈值部分的参数通过遗传算法进行计算机优化。 在放射科医师首次接受或拒绝系统报告的个体检测之后，将该系统的结果与放射科医师对原始乳房X线照片的观察结合在一起，结合观察结果与结果。

    Method for combining automated detections from medical images with observed detections of a human interpreter
    6.
    发明授权
    Method for combining automated detections from medical images with observed detections of a human interpreter 失效
    用于将来自医学图像的自动检测与观察到的人类解释器的检测相结合的方法

    公开(公告)号：US06556699B2

    公开(公告)日：2003-04-29

    申请号：US09938908

    申请日：2001-08-24

    申请人： Steven K. Rogers ,  Philip Amburn ,  Telford S. Berkey ,  Randy P. Broussard ,  Martin P. DeSimio ,  Jeffrey W. Hoffmeister ,  Edward M. Ochoa ,  Thomas P. Rathbun ,  John E. Rosenstengel

    发明人： Steven K. Rogers ,  Philip Amburn ,  Telford S. Berkey ,  Randy P. Broussard ,  Martin P. DeSimio ,  Jeffrey W. Hoffmeister ,  Edward M. Ochoa ,  Thomas P. Rathbun ,  John E. Rosenstengel

    IPC分类号： G06K900

    CPC分类号： B25J15/04 ,  A61B6/502 ,  B29C49/0021 ,  B29C2791/006 ,  B29C2791/007 ,  B29L2023/18 ,  G06K9/38 ,  G06K9/4609 ,  G06K9/6254 ,  G06K2209/05 ,  G06T5/20 ,  G06T7/0012 ,  Y10S128/922

    摘要： A method and system for detecting and displaying clustered microcalcifications in a digital mammogram, wherein a single digital mammogram is first automatically cropped to a breast area sub-image which is then processed by means of an optimized Difference of Gaussians filter to enhance the appearance of potential microcalcifications in the sub-image. The potential microcalcifications are thresholded, clusters are detected, features are computed for the detected clusters, and the clusters are classified as either suspicious or not suspicious by means of a neural network. Thresholding is preferably by sloping local thresholding, but may also be performed by global and dual-local thresholding. The locations in the original digital mammogram of the suspicious detected clustered microcalcifications are indicated. Parameters for use in the detection and thresholding portions of the system are computer-optimized by means of a genetic algorithm. The results of the system are optimally combined with a radiologist's observation of the original mammogram by combining the observations with the results, after the radiologist has first accepted or rejected individual detections reported by the system.

    摘要翻译： 一种用于在数字乳腺X线照片中检测和显示聚类微钙化的方法和系统，其中首先将单个数字乳腺X线照片自动裁剪到乳房区域子图像，然后通过优化的高斯差分滤波器处理以增强潜在的外观 子图像中的微钙化。 潜在的微钙化被阈值化，检测到簇，为检测到的簇计算特征，并且通过神经网络将簇分类为可疑的或不可疑的。 阈值优选地通过倾斜的局部阈值来进行，但是也可以通过全局和双局部阈值来执行。 指出了可疑检测到的聚集微量钙化的原始数字乳腺X线照片中的位置。 用于系统的检测和阈值部分的参数通过遗传算法进行计算机优化。 在放射科医师首次接受或拒绝系统报告的个体检测之后，将该系统的结果与放射科医师对原始乳房X线照片的观察结合在一起，结合观察结果与结果。

    Joint optimization of parameters for the detection of clustered microcalcifications in digital mammograms
    8.
    发明授权
    Joint optimization of parameters for the detection of clustered microcalcifications in digital mammograms 失效
    联合优化数字乳腺X线照片检测聚类微钙化参数

    公开(公告)号：US06389157B2

    公开(公告)日：2002-05-14

    申请号：US09758889

    申请日：2001-01-11

    申请人： Steven K. Rogers ,  Randy P. Broussard ,  Edward M. Ochoa ,  Thomas F. Rathbun ,  John E. Rosenstengel

    发明人： Steven K. Rogers ,  Randy P. Broussard ,  Edward M. Ochoa ,  Thomas F. Rathbun ,  John E. Rosenstengel

    IPC分类号： G06K900

    CPC分类号： B25J15/04 ,  A61B6/502 ,  B29C49/0021 ,  B29C2791/006 ,  B29C2791/007 ,  B29L2023/18 ,  G06K9/38 ,  G06K9/4609 ,  G06K9/6254 ,  G06K2209/05 ,  G06T5/20 ,  G06T7/0012 ,  Y10S128/922

    摘要： A method and system for detecting and displaying clustered microcalcifications in a digital mammogram, wherein a single digital mammogram is first automatically cropped to a breast area sub-image which is then processed by means of an optimized Difference of Gaussians filter to enhance the appearance of potential microcalcifications in the sub-image. The potential microcalcifications are thresholded, clusters are detected, features are computed for the detected clusters, and the clusters are classified as either suspicious or not suspicious by means of a neural network. Thresholding is preferably by sloping local thresholding, but may also be performed by global and dual-local thresholding. The locations in the original digital mammogram of the suspicious detected clustered microcalcifications are indicated. Parameters for use in the detection and thresholding portions of the system are computer-optimized by means of a genetic algorithm. The results of the system are optimally combined with a radiologist's observation of the original mammogram by combining the observations with the results, after the radiologist has first accepted or rejected individual detections reported by the system.

    摘要翻译： 一种用于在数字乳腺X线照片中检测和显示聚类微钙化的方法和系统，其中首先将单个数字乳腺X线照片自动裁剪到乳房区域子图像，然后通过优化的高斯差分滤波器处理以增强潜在的外观 子图像中的微钙化。 潜在的微钙化被阈值化，检测到簇，为检测到的簇计算特征，并且通过神经网络将簇分类为可疑的或不可疑的。 阈值优选地通过倾斜的局部阈值来进行，但是也可以通过全局和双局部阈值来执行。 指出了可疑检测到的聚集微量钙化的原始数字乳腺X线照片中的位置。 用于系统的检测和阈值部分的参数通过遗传算法进行计算机优化。 在放射科医师首次接受或拒绝系统报告的个体检测之后，将该系统的结果与放射科医师对原始乳房X线照片的观察结合在一起，结合观察结果与结果。

    Gabor filtering for improved microcalcification detection in digital mammograms
    9.
    发明授权
    Gabor filtering for improved microcalcification detection in digital mammograms 有权
    Gabor滤波，用于改进数字乳腺X线照片中的微钙化检测

    公开(公告)号：US6137898A

    公开(公告)日：2000-10-24

    申请号：US200128

    申请日：1998-11-25

    申请人： Randy P. Broussard ,  Thomas F. Rathbun ,  Steven K. Rogers

    发明人： Randy P. Broussard ,  Thomas F. Rathbun ,  Steven K. Rogers

    IPC分类号： A61B6/00 ,  G06K9/38 ,  G06K9/62 ,  G06T5/20 ,  G06T7/00 ,  G06K9/00

    CPC分类号： B29C49/0021 ,  B25J15/04 ,  G06K9/38 ,  G06K9/4609 ,  G06K9/6254 ,  G06T5/20 ,  G06T7/0012 ,  G06T7/402 ,  A61B6/502 ,  B29C2791/006 ,  B29C2791/007 ,  B29L2023/18 ,  G06K2209/05 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20141 ,  G06T2207/30068

    摘要： A method and system for detecting and displaying clustered microcalcifications in a digital mammogram, wherein a single digital mammogram is first automatically cropped to a breast area sub-image which is then processed by means of an optimized Difference of Gaussians filter to enhance the appearance of potential microcalcifications in the sub-image. The potential microcalcifications are thresholded, clusters are detected, features are computed for the detected clusters, and the clusters are classified as either suspicious or not suspicious by means of a neural network. Thresholding is preferably by sloping local thresholding, but may also be performed by global and dual-local thresholding. The locations in the original digital mammogram of the suspicious detected clustered microcalcifications are indicated. Parameters for use in the detection and thresholding portions of the system are computer-optimized by means of a genetic algorithm. The results of the system are optimally combined with a radiologist's observation of the original mammogram by combining the observations with the results, after the radiologist has first accepted or rejected individual detections reported by the system. An alternative embodiment reduces false positive detections by means of Gabor filtering the cropped mammogram image to identify elongated structures such as milk ducts and veins. Individual microcalcifications coincident with the elongated structures are removed and the remaining detections grouped into clusters.

    摘要翻译： 一种用于在数字乳腺X线照片中检测和显示聚类微钙化的方法和系统，其中首先将单个数字乳腺X线照片自动裁剪到乳房区域子图像，然后通过优化的高斯差分滤波器处理以增强潜在的外观 子图像中的微钙化。 潜在的微钙化被阈值化，检测到簇，为检测到的簇计算特征，并且通过神经网络将簇分类为可疑的或不可疑的。 阈值优选地通过倾斜的局部阈值来进行，但是也可以通过全局和双局部阈值来执行。 指出了可疑检测到的聚集微量钙化的原始数字乳腺X线照片中的位置。 用于系统的检测和阈值部分的参数通过遗传算法进行计算机优化。 在放射科医师首次接受或拒绝系统报告的个体检测之后，将该系统的结果与放射科医师对原始乳房X线照片的观察结合在一起，结合观察结果与结果。 替代实施例通过Gabor过滤裁剪的乳房X线透射图像来减少假阳性检测以识别细长结构，例如乳管和静脉。 与细长结构重合的单个微钙化被去除，剩余的检测被分组成簇。