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An automated method and system for selecting a region of interest and detecting a septum in a digital chest radiograph

机译:一种自动方法和系统,用于在数字胸部放射线照片中选择目标区域并检测隔垫

摘要

An automated method and system for discriminating between normal lungs and abnormal lungs having interstitial disease and/or septal lines, wherein a large number of adjacent regions of interest (ROIs) are selected, corresponding to an area on a digital image of a patient's lungs. The ROIs each contain a number of square or rectangular pixel arrays and are selected to sequentially fill in the total selected area of the lungs to be analyzed. A background trend is removed from each individual ROI and the ROIs are then analyzed to determine those exhibiting sharp edges, i.e., high edge gradients. A percentage of these sharp-edged ROIs are removed from the original sample based on the edge gradient analysis, a majority of which correspond to rib-edge containing ROIs. After removal of the sharp-edged ROIs, texture measurements are taken on the remaining sample in order to compare such data with predetermined data for normal and abnormal lungs. Thus, a computerized scheme for quantitative analysis of interstitial lung diseases and/or septal lines appearing in digitized chest radiographs can be implemented in practical clinical situations.
机译:一种自动方法和系统,用于区分正常肺和具有间质性疾病和/或中隔线的异常肺,其中选择了大量相邻的感兴趣区域(ROI),这些区域对应于患者肺部数字图像上的区域。每个ROI包含许多正方形或矩形像素阵列,并被选择以顺序填充要分析的肺的总选定区域。从每个单独的ROI中去除背景趋势,然后分析ROI以确定那些具有锐利边缘,即高边缘梯度的ROI。根据边缘梯度分析,从原始样品中删除了这些锐利的ROI的百分比,其中大部分对应于包含肋骨的ROI。去除锐利的ROI后,对剩余的样品进行质构测量,以便将此类数据与正常和异常肺部的预定数据进行比较。因此,可以在实际临床情况下实施一种计算机化方案,用于定量分析数字化胸部X线照片中出现的间质性肺疾病和/或中隔线。

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