基于遗传算法的形态学医学图像滤波

Morphology medical image filtering based on genetic algorithm

滤波是医学图像处理的重要前期基础。针对形态学滤波的局限性,提出一种基于遗传算法的形态学滤波方法,该方法通过构造适当的适应度函数和对噪声样本图像的学习,利用遗传算法对结构元素的大小和形状以及中值滤波窗口进行自适应调整,找出最优的中值滤波窗和结构元素组合,从而获得最优的滤波效果。实验结果表明使用这一方法滤波后的医学图像信噪比得到了明显提高。

Filtering is a very important preprocessing procedure for medical image. For the limitation of morphology filtering, the paper proposes genetic algorithm-based morphology filtering. First constructs appropriate fitness function and learned sample noise image, then adjusts adaptively the size and shape of structure elements and the median filtering window by genetic algorithm, the optimized combination of median filtering windows and structure elements is found ,which can filter the medical image efficiently. The experimental result shows that the signal noise ratio of filtered medical image increases more by the proposed novel method than by morphology filtering and median filtering.