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Sclerotic rib metastases detection on routine CT images

机译:常规CT图像上的硬化性肋骨转移检测

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This work presents a computer-aided detection (CAD) system to aid radiologists in finding sclerotic bone metastases in the ribs on routine body imaging CT protocols with 5mm chest/abdomen CT images. First, the spine is segmented to locate the ribs using thresholding, region growing and a vertebra template. The centerlines of ribs are then traced by a progressive algorithm based on maximizing the cross-section overlap. The profile of the ribs along the centerline is analyzed to generate the initial detections. A set of quantitative features is then extracted and sent to a support vector machine for classification. Novel visualization techniques are also developed to display all ribs and the distribution of bone lesions in one single view. The system was tested on 10 data sets with 185 sclerotic lesions identified by an expert. A leave-one-out cross-validation results in 75.4% sensitivity at an average of 5.6 false positives per case.
机译:这项工作提出了一种计算机辅助检测(CAD)系统,以帮助放射科医生根据常规的5mm胸部/腹部CT图像进行CT成像,以发现肋骨中的硬化性骨转移。首先,使用阈值分割,区域生长和椎骨模板将脊椎分段以定位肋骨。然后,通过基于最大化横截面重叠的渐进算法来跟踪肋骨的中心线。分析沿中心线的肋骨轮廓,以生成初始检测结果。然后提取一组定量特征并将其发送到支持向量机进行分类。还开发了新颖的可视化技术,以在单个视图中显示所有肋骨和骨病变的分布。该系统在10个数据集上进行了测试,这些数据集由专家鉴定了185个硬化性病变。留一法交叉验证的结果是75.4%的灵敏度,每例平均出现5.6个假阳性。

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