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1. 发明授权

US06763128B1 Method for analyzing detections in a set of digital images using case based normalcy classification 有权
标题翻译：使用基于案例的正常分类来分析一组数字图像中的检测的方法
公开(公告)号：US06763128B1
公开(公告)日：2004-07-13
申请号：US10461316
申请日：2003-06-13
申请人： Steven K. Rogers , Michael J. Collins , Richard A. Mitchell
发明人： Steven K. Rogers , Michael J. Collins , Richard A. Mitchell
IPC分类号： B06K900
CPC分类号： G06K9/6293 , G06K9/4609 , G06K9/56 , G06K2209/05 , G06T7/0012 , G06T2207/30068
摘要： A computer aided detection method and system to assist radiologists in the reading of medical images. The method and system has particular application to the area of mammography including detection of clustered microcalcifications and densities. A microcalcification detector is provided wherein individual detections are rank ordered and classified, and one of the features for classification is derived using a multilayer perceptron. A density detector is provided including an iterative, dynamic region growing module with embedded subsystem for rank ordering and classification of a best subset of candidate masks. A post processing stage is provided where detections are analyzed in the context of a set of images for a patient. The post processing includes a normalcy classification including providing computed values corresponding to each detection from a category of detections on an image set, computing a normalcy value using the computed values, and removing all detections from an image set when the normalcy value does not meet a predetermined condition. The final output of the system is a set of indications overlaid on the input medical images.
摘要翻译：一种计算机辅助检测方法和系统，用于帮助放射科医师阅读医学图像。该方法和系统在乳腺摄影领域具有特殊应用，包括检测聚类微钙化和密度。提供了一种微钙化检测器，其中单独的检测是排序和分类的，并且使用多层感知器导出用于分类的特征之一。提供了一种密度检测器，其包括具有嵌入式子系统的迭代动态区域增长模块，用于对候选掩模的最佳子集进行排序和分类。提供后处理阶段，其中在用于患者的一组图像的上下文中分析检测。后处理包括正常分类，包括从图像集中的检测类别提供与每个检测相对应的计算值，使用计算值计算正常值，以及当正常值不满足时从图像集中移除所有检测预定条件。系统的最终输出是覆盖在输入医学图像上的一组指示。

2. 发明授权

US06757415B1 Method for determining features from detections in a digital image using a bauer-fisher ratio 有权
标题翻译：一种使用鲍尔 - 比勒比法从数字图像检测中确定特征的方法
公开(公告)号：US06757415B1
公开(公告)日：2004-06-29
申请号：US10461301
申请日：2003-06-13
申请人： Steven K. Rogers , Kenneth W. Bauer , Michael J. Collins , Martin P. DeSimio , Richard A. Mitchell
发明人： Steven K. Rogers , Kenneth W. Bauer , Michael J. Collins , Martin P. DeSimio , Richard A. Mitchell
IPC分类号： G06K900
CPC分类号： G06K9/6293 , G06K9/4609 , G06K9/56 , G06K2209/05 , G06T7/0012 , G06T2207/30068
摘要： A computer aided detection method and system to assist radiologists in the reading of medical images. The method and system has particular application to the area of mammography including detection of clustered microcalcifications and densities. A microcalcification detector is provided wherein individual detections are rank ordered and classified, and one of the features for classification is derived using a multilayer perceptron. A density detector is provided including an iterative, dynamic region growing module with embedded subsystem for rank ordering and classification of a best subset of candidate masks. Features are computed from a detection on an input image by providing first and second regions on the input image corresponding to areas inside and outside the detection, measurements are computed based on values derived from the two regions, a standard deviation is computed for the measurements in each region, and a feature for the detection is computed using a Bauer-Fisher ratio. A post processing stage is provided where detections are analyzed in the context of a set of images for a patient. The final output of the system is a set of indications overlaid on the input medical images.
摘要翻译：一种计算机辅助检测方法和系统，用于帮助放射科医师阅读医学图像。该方法和系统在乳腺摄影领域具有特殊应用，包括检测聚类微钙化和密度。提供了一种微钙化检测器，其中单独的检测是排序和分类的，并且使用多层感知器导出用于分类的特征之一。提供了一种密度检测器，其包括具有嵌入式子系统的迭代动态区域增长模块，用于对候选掩模的最佳子集进行排序和分类。通过在对应于检测内部和外部的区域的输入图像上提供第一和第二区域来对输入图像上的检测计算特征，根据从两个区域导出的值来计算测量值，计算标准偏差每个区域和用于检测的特征使用鲍尔 - 费雪比来计算。提供后处理阶段，其中在用于患者的一组图像的上下文中分析检测。系统的最终输出是覆盖在输入医学图像上的一组指示。

3. 发明授权

US06801645B1 Computer aided detection of masses and clustered microcalcifications with single and multiple input image context classification strategies 有权
标题翻译：计算机辅助检测群体和群集微钙化与单输入和多输入图像上下文分类策略
公开(公告)号：US06801645B1
公开(公告)日：2004-10-05
申请号：US09602762
申请日：2000-06-23
申请人： Michael J. Collins , Steven K. Rogers , Richard A. Mitchell
发明人： Michael J. Collins , Steven K. Rogers , Richard A. Mitchell
IPC分类号： G06K900
CPC分类号： G06K9/6293 , G06K9/4609 , G06K9/56 , G06K2209/05 , G06T7/0012 , G06T2207/30068
摘要： A computer aided detection method and system to assist radiologists in the reading of medical images. The method and system has particular application to the area of mammography including detection of clustered microcalcifications and densities. A microcalcification detector is provided wherein individual detections are rank ordered and classified, and one of the features for classification is derived using a multilayer perceptron. A density detector is provided including an iterative, dynamic region growing module with embedded subsystem for rank ordering and classification of a best subset of candidate masks. A post processing stage is provided where detections are analyzed in the context of a set of images for a patient. Three analysis methods are used to distribute a limited number of detections across the image set and further within each image, and additionally to perform a normalcy classification. The normalcy classification is used to remove all detections from an image set when predetermined normalcy conditions are met. The final output of the system is a set of indications overlaid on the input medical images.
摘要翻译：一种计算机辅助检测方法和系统，用于帮助放射科医师阅读医学图像。该方法和系统在乳腺摄影领域具有特殊应用，包括检测聚类微钙化和密度。提供了一种微钙化检测器，其中单独的检测是排序和分类的，并且使用多层感知器导出用于分类的特征之一。提供了一种密度检测器，其包括具有嵌入式子系统的迭代动态区域增长模块，用于对候选掩模的最佳子集进行排序和分类。提供后处理阶段，其中在用于患者的一组图像的上下文中分析检测。三种分析方法用于跨越图像集并且进一步在每个图像内分布有限数量的检测，并且另外执行正常分类。当满足预定的正常条件时，正常分类用于从图像集中去除所有检测。系统的最终输出是覆盖在输入医学图像上的一组指示。

4. 发明授权

US06778941B1 Message and user attributes in a message filtering method and system 有权
标题翻译：消息过滤方法和系统中的消息和用户属性
公开(公告)号：US06778941B1
公开(公告)日：2004-08-17
申请号：US10010789
申请日：2001-11-13
申请人： Steven W. Worrell , Steven K. Rogers , Matthew Kabrisky , Philip Amburn
发明人： Steven W. Worrell , Steven K. Rogers , Matthew Kabrisky , Philip Amburn
IPC分类号： G04F100
CPC分类号： H04L67/30 , G06Q10/107 , H04L29/06 , H04L51/12 , H04L69/329
摘要： A method and system for filtering messages where the importance of a message is determined by analyzing the message body in conjunction with message attributes. Message body refers to the text in the body of the message, whereas message attributes convey information about the message. In another embodiment, analysis of the user's current computing environment provides additional input to the filtering system. This allows for preferentially weighting messages of user's current interests. Analysis includes computation of feature vectors and subsequent input to a discriminant function. The discriminant function provides a test statistic which is compared to a threshold. If the test statistic exceeds the threshold, the incoming message is passed by the filtering system and may be displayed to the user. In another embodiment, message body and attributes are used to anticipate significant events in a time series, such as streaming financial data.
摘要翻译：用于过滤消息的方法和系统，其中消息的重要性通过与消息属性一起分析消息体来确定。消息体指的是消息体中的文本，而消息属性传达关于消息的信息。在另一个实施例中，用户当前计算环境的分析为过滤系统提供附加输入。这允许优先权衡用户当前兴趣的消息。分析包括特征向量的计算和随后到判别函数的输入。判别函数提供与阈值进行比较的检验统计量。如果测试统计信息超过阈值，则传入消息由过滤系统传递，并可能显示给用户。在另一个实施例中，消息体和属性用于预测时间序列中的重要事件，诸如流媒体财务数据。

5. 发明授权

US06970587B1 Use of computer-aided detection system outputs in clinical practice 失效
标题翻译：在临床实践中使用计算机辅助检测系统输出
公开(公告)号：US06970587B1
公开(公告)日：2005-11-29
申请号：US10674232
申请日：2003-09-29
申请人： Steven K. Rogers
发明人： Steven K. Rogers
IPC分类号： G06K9/00 , G06T7/00
CPC分类号： G06T7/0012 , G06T2207/30068 , Y10S128/922
摘要： The present invention provides for the use of computer-aided detection (CAD) system output displays for providing accurate representations of areas for subsequent exams. Since the CAD output, unlike the original medical imagery, is not used during the initial reading, the radiologist does not mark it until a final determination is reached regarding subsequent procedures. Additionally, since the CAD output contains versions of the original imagery, the regions indicated by the radiologist are shown in the context of the particular anatomical detail for the given patient. This detail assists the technologist in more efficiently and accurately locating the exact area for subsequent exams.
摘要翻译：本发明提供了使用计算机辅助检测（CAD）系统输出显示器来提供后续检查的区域的准确表示。由于CAD输出与原始医学影像不同，在初始阅读期间不使用放射科医生，因此放射科医生在对后续程序达成最终确定之前不会进行标记。另外，由于CAD输出包含原始图像的版本，所以放射科医师指示的区域显示在给定患者的具体解剖细节的上下文中。这个细节帮助技术人员更有效和准确地确定后续考试的确切区域。

6. 发明授权

US08756693B2 Malware target recognition 有权
标题翻译：恶意软件目标识别
公开(公告)号：US08756693B2
公开(公告)日：2014-06-17
申请号：US13438240
申请日：2012-04-03
申请人： Thomas E. Dube , Richard A. Raines , Steven K. Rogers
发明人： Thomas E. Dube , Richard A. Raines , Steven K. Rogers
IPC分类号： G06F11/00
CPC分类号： G06F21/564
摘要： A method, apparatus and program product are provided to recognize malware in a computing environment having at least one computer. A sample is received. An automatic determination is made by the at least one computer to determine if the sample is malware using static analysis methods. If the static analysis methods determine the sample is malware, dynamic analysis methods are used by the at least one computer to automatically determine if the sample is malware. If the dynamic analysis methods determine the sample is malware, the sample is presented to a malware analyst to adjudicate the automatic determinations of the static and dynamic analysis. If the adjudication determines the sample is malware, a response action is initiated to recover from or mitigate a threat of the sample.
摘要翻译：提供了一种方法，装置和程序产品以在具有至少一个计算机的计算环境中识别恶意软件。收到样品。由至少一台计算机进行自动确定，以使用静态分析方法确定样本是否为恶意软件。如果静态分析方法确定样品是恶意软件，则至少一台计算机使用动态分析方法自动确定样品是否为恶意软件。如果动态分析方法确定样本是恶意软件，则会将示例呈现给恶意软件分析师，以判断静态和动态分析的自动确定。如果裁决确定样本是恶意软件，则启动响应操作以恢复或减轻样本的威胁。

7. 发明授权

US06401082B1 Autoassociative-heteroassociative neural network 失效
标题翻译：自动关联 - 异质关联神经网络
公开(公告)号：US06401082B1
公开(公告)日：2002-06-04
申请号：US09434549
申请日：1999-11-08
申请人： Claudia V. Kropas-Hughes , Steven K. Rogers , Mark E. Oxley , Matthew Kabrisky
发明人： Claudia V. Kropas-Hughes , Steven K. Rogers , Mark E. Oxley , Matthew Kabrisky
IPC分类号： G06N300
CPC分类号： G06K9/6248 , G06N3/0454
摘要： An efficient neural network computing technique capable of synthesizing two sets of output signal data from a single input signal data set. The method and device of the invention involves a unique integration of autoassociative and heteroassociative neural network mappings, the autoassociative neural network mapping enabling a quality metric for assessing the generalization or prediction accuracy of the heteroassociative neural network mapping.
摘要翻译：一种能够从单个输入信号数据集合成两组输出信号数据的高效神经网络计算技术。本发明的方法和装置涉及自动关联和异质关联神经网络映射的独特集成，自动关联神经网络映射能够实现用于评估异质关联神经网络映射的泛化或预测精度的质量度量。

8. 发明授权

US06389157B2 Joint optimization of parameters for the detection of clustered microcalcifications in digital mammograms 失效
标题翻译：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。

9. 发明授权

US06205236B1 Method and system for automated detection of clustered microcalcifications from digital mammograms 失效
标题翻译：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。

10. 发明授权

US6091841A Method and system for segmenting desired regions in digital mammograms 有权
标题翻译：用于分割数字乳腺X线照片中所需区域的方法和系统
公开(公告)号：US6091841A
公开(公告)日：2000-07-18
申请号：US418383
申请日：1999-10-14
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： A61B6/00 , B25J15/04 , B29C49/00 , F16L11/11 , F16L11/22 , G06K9/38 , G06K9/46 , G06K9/62 , G06T1/00 , G06T5/20 , G06T7/00 , G06K9/36
CPC分类号： B25J15/04 , B29C49/0021 , G06K9/38 , G06K9/4609 , G06K9/6254 , G06T5/20 , G06T7/0012 , A61B6/502 , B29C2791/006 , B29C2791/007 , B29L2023/18 , G06K2209/05 , 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。

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