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Method for determining features from detections in a digital image using a bauer-fisher ratio

机译:使用鲍尔-费舍尔比从数字图像中的检测确定特征的方法

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.
机译:一种计算机辅助检测方法和系统,可帮助放射科医生读取医学图像。该方法和系统在乳腺摄影领域具有特殊的应用,包括检测成簇的微钙化和密度。提供了一种微钙化检测器,其中各个检测是按顺序排列和分类的,并且用于分类的特征之一是使用多层感知器得出的。提供了密度检测器,其包括具有嵌入式子系统的迭代动态区域增长模块,用于对候选蒙版的最佳子集进行等级排序和分类。通过在输入图像上提供与检测范围内外的区域相对应的第一和第二区域,根据输入图像上的检测结果计算特征,并根据从这两个区域得出的值计算出测量结果,并为测量结果计算标准差每个区域,并使用Bauer-Fisher比计算检测特征。提供了后处理阶段,其中在针对患者的一组图像的情况下分析检测。系统的最终输出是覆盖在输入医学图像上的一组指示。

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