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一种在医学图像中挖掘非对称区域的方法

Efficient Local Asymmetric Region Detection in Medical Images

  • 摘要: 提出一种利用图像刚性配准算法和数字形态学调整近似对称区域、有效挖掘出图像非对称区域,并自动判断头部炎症类疾病的算法.首先扩展适用于二值图像的自反射刚性配准算法到灰度医学图像上,然后对配准后的图像使用条件腐蚀算子调整那些近似对称区域的边界,在不同的精度下进行迭代以获得最终的非对称区域.在人类头部CT的胆脂瘤检测实验中,该方法显示出良好的挖掘效果,检测成功率达到95%.

     

    Abstract: A novel method is presented for efficient local asymmetric regions detection in medical images using image registration and mathematical morphology.First,we extend self-reflexive rigid binary image registration to find the symmetry plane of a gray-scale medical image.Then based on the registered image, a fast conditional erosion operator is used to adjust the border of bones and brain tissues to remove the likely symmetric region.These two steps are iteratively repeated using a mult-i resolution scheme to extract the final interesting area. The experiment to detect cholesteatoma in human head CT based on the proposed method shows encouraging results,and 95% of the asymmetric regions are correctly detected.

     

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