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    • 4. 发明授权
    • Method and system for detecting small structures in images
    • 用于检测图像中小结构的方法和系统
    • US06738500B2
    • 2004-05-18
    • US10227733
    • 2002-08-26
    • Isaac N. BankmanLloyd W. Ison
    • Isaac N. BankmanLloyd W. Ison
    • G06K900
    • G06K9/342G06K2209/053G06T7/0012G06T7/11G06T7/187G06T2207/10116G06T2207/20101G06T2207/20156G06T2207/30068G06T2207/30096
    • The invention is a method and apparatus for automated detection of small structures in images. One specific use is to detect malignant microcalcification clusters in mammograms. A digitized and filtered mammogram image is stored in a computer. Seed pixels, which are pixels that are brighter than their immediate neighbors, are identified to indicate candidate structures and used to construct two regions. Various features are then measured using the two regions around each seed point. The features characterize each candidate structure and are input to a classifier, such as a neural network. The classifier then distinguishes between structures of interest and background. The structures detected by the classifier are then presented to a clustering algorithm. A detected structure that is less than a threshold distance away from the nearest structure and a cluster is included in that cluster. Finally, the results are displayed, either on a monitor or on hard copy, with a frame around the detected cluster.
    • 本发明是用于图像中小结构自动检测的方法和装置。 一个具体用途是检测乳腺X线照片中的恶性微钙化簇。 数字化和过滤的乳房X线照片图像存储在计算机中。 识别比其直接邻居更亮的像素的种子像素,以指示候选结构并用于构建两个区域。 然后使用每个种子点周围的两个区域测量各种特征。 这些特征表征每个候选结构,并被输入到诸如神经网络之类的分类器。 然后,分类器区分感兴趣的结构和背景。 然后将分类器检测到的结构呈现给聚类算法。 检测到的结构小于距离最近结构的阈值距离,并且集群中包含集群。 最后,结果将在监视器或硬拷贝上显示,并检测到集群周围的框架。