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Automated Calculation Of Bifurcation Carotid Angle For Analyzing The Risk Of Carotis Plaques By Using Carotid Ct Angiographic Images

机译:用CORID CT血管造影图像分析分叉颈动脉角分析Carotis斑块的风险的自动计算

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The aim of this study is calculation of bifurcation carotid angle by detection of vessel boundaries to assist the medical doctors if this angle is a risk factor about formation of carotid plaques.Carotid ct angiography images are clustered automatically by ISODATA unsupervised classification algorithm. Since the spectral digital numbers (DN) of vessel pixels are bigger than the other part of the images, the cluster which has the biggest median value of DN among all other classes gives the vessel class. The cluster image in raster format is converted into the vector format which allows working on the vessel geometry. The converted vector vessel cluster dataset has been simplified using Douglas-Peucker algorithm to eliminate the zigzag effects of pixel data which are remained on the vector form dataset. Then the cluster polygon is converted to lines and the vertices which will be used for the calculation of bifurcation carotid angle. For sorting the vertex points to calculate the angle on each vertex, alpha-shapes algorithm is applied along the boundary. Then all the angles on each vertex point along the boundary of vessels are calculated. It is also visually clear that the angle which has the minimum value among all the calculated angles, gives the bifurcation carotid angle for one projected plane. The final carotid angle has calculated and 18 sample datasets are used to test the method.
机译:本研究的目的是通过检测血管边界来计算分叉颈动脉角,以帮助医学医生,如果该角度是关于形成颈动脉斑块的危险因素。通过ISODATA无监督分类算法自动聚类CAROTID CT血管造影图像。由于血管像素的光谱数字数(DN)大于图像的另一个部分,因此在所有其他类别中具有DN最大的值的群集给予血管类。栅格格式中的群集图像被转换为​​载体格式,允许在船只几何上工作。使用Douglas-Peucker算法简化了转换的矢量船只集群数据集,以消除像素数据的Zigzag效果,该Zigzag效果保留在矢量表单数据集上。然后,簇多边形被转换为线条和顶点,该顶点将用于计算分叉颈动脉角度。为了对顶点点进行排序以计算每个顶点上的角度,沿边界应用alpha形算法。然后计算沿着血管边界的每个顶点点上的所有角度。它还目视清楚地清楚的是,在所有计算的角度之间具有最小值的角度,给出一个投影平面的分叉颈动脉角。已经计算出最终的颈动脉角,并且使用18个样品数据集来测试该方法。

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