改进的遗传算法在医学图像中的应用  

Application of improved genetic algorithm in medical image

作　　者：梁文宇[1] 龚涛[1] 吴宇翔[1] 

机构地区：[1]东华大学信息技术与工程学院,上海201600

出　　处：《传感器与微系统》2016年第10期152-154,共3页Transducer and Microsystem Technologies

摘　　要：针对标准的遗传算法(GA)在优化Otsu法求取图像阈值时出现收敛速度慢、易早熟等问题,提出了一种改进的GA用于图像分割。该算法根据种群不同的进化代数和个体适应度的大小,动态地调整精英选择策略和遗传算子,从而提高了算法的收敛速度、得到了范围稳定的图像分割阈值,且保持了种群多样性。将该算法应用于医学图像分割,实验结果表明:该算法可以对医学图像进行分割且效果明显。Aiming at problem of low speed of convergence,early mature of standard genetic algorithm（ GA） occur in optimizing Otsu method to search for threshold of image,an improved GA for image segmentation is proposed.According to different evolution generation and individual fitness,this improved GA can adjust strategies of elite selection and genetic operator dynamically,so it not only can speed up the convergence speed,but also can get image segmentation threshold with stable range and keep diversity of population. This algorithm is used in medical image segmentation,and experimental results show that the algorithm can be used for segmentation of medical image and effect is obvious.

关 键 词：遗传算法 图像分割 阈值 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]