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Automatic Calibration Marker Detection for Radiography Images

机译:放射线图像的自动校准标记检测

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In this paper we analyse the possibility of simple detection of circular radiography markers. To detect the marker, we utilised the Hough transform. Two approaches were analysed: with detecting image edges and without image edge detection where pixel gradient was used in Hough voting process, i.e. to increase the accumulator values. Approaches were evaluated on 13 clinical radiography images. It was shown that approach that detects image edges spatially matches the reference circles only 0.22 % less than manual annotation values, whereas approach that uses just the gradient magnitudes spatially matches the reference circles 3.2 % less than manual annotations.
机译:在本文中,我们分析了简单检测圆形射线照相标记物的可能性。为了检测标记,我们利用了霍夫变换。分析了两种方法:具有检测图像边缘和不具有图像边缘检测的情况,其中在霍夫投票过程中使用像素梯度,即,以增加累加器值。方法对13幅临床放射线图像进行了评估。结果表明,检测图像边缘的方法在空间上匹配参考圆仅比手动标注少0.22%,而仅使用梯度幅度的方法在空间上匹配参考圆比手动标注少3.2%。

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