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首页> 外文会议>Image Processing pt.3; Progress in Biomedical Optics and Imaging; vol.7 no.30 >Mammographic CADx System using an Image Library with an Intelligent Agent: A Pattern Matching Approach
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Mammographic CADx System using an Image Library with an Intelligent Agent: A Pattern Matching Approach

机译：使用带有智能代理的图像库的乳腺X射线摄影CAD系统：一种模式匹配方法

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It is conceivable that a comprehensive clinical case library with intelligent agents can sort and render clinically similar cases and present clinically significant features to assist the radiologist in interpreting mammograms. In this study, we used a deformable vector diagram as the primary framework for matching the mammographic masses. The vector diagram provides gradient and shape features of the mass. The deformable algorithm allows flexible matching. The vector diagram was also incorporated with our newly developed delineation method using steepest changes of a probability based cost-function. Thus it allows us to automatically extract the main body and significant part of border region for pattern matching using a weighted mutual information technique. We have collected 86 mammograms. Of these cases, 46 contain a benign mass and the other 40 contain a malignant mass. Using the weighted mutual information technique on the vector diagram of the mass region, we found that the benign masses can be sorted into 6 groups except one case; the malignant masses can be sorted into 8 groups except two cases. For all 86 cases, the masses can be sorted into 13 groups except three cases. In addition, one group of benign masses and one group of malignant mass cases merged into one which contains 10 cases. Hence, the success sorting rate was 85.7% (12/14) in terms of group and was 84.9% (73/86) in terms of case, respectively.
机译：可以想象，具有智能代理的综合临床病例库可以对临床相似的病例进行分类和呈现，并呈现出临床上的重要特征，以帮助放射科医生解释乳房X线照片。在这项研究中，我们使用可变形矢量图作为匹配乳房X线摄影质量的主要框架。矢量图提供了质量的梯度和形状特征。可变形算法允许灵活匹配。使用基于概率的成本函数的最陡峭变化，矢量图还与我们新开发的描绘方法结合在一起。因此，它允许我们使用加权互信息技术自动提取主体和边界区域的重要部分以进行模式匹配。我们已经收集了86个乳房X线照片。在这些情况中，46个包含良性肿块，其他40个包含恶性肿块。利用加权互信息技术在质量区域矢量图上发现，除了一种情况外，良性肿块可分为6组。除两种情况外，恶性肿块可分为8组。对于全部86例，除三例外，群众可分为13组。此外，一组良性肿块和一组恶性肿块病例合并为一个包含10个病例的病例。因此，就分组而言，成功分类率为85.7％（12/14），按案件而言，则为84.9％（73/86）。

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