为了降低甲状腺肿瘤的误诊率和漏诊率,提出将甲状腺肿瘤的SPECT图像和B超图像进行多模异机融合,提供涵盖功能信息和结构信息的融合后图像,为手术规划和放射治疗提供依据.配准是融合的前提,针对2种成像模式的不同特点,采用阈值方法和图割方法提取轮廓并填充为二值图像,建立仿射变换模型对待配准图像进行变换,将混合蛙跳算法引入基于特征的配准过程中,将局部区域的二值图像的互信息量作为适应度函数以获取水平平移量、垂直平移量和旋转角度的全局最优解.实验表明,该算法具有参数少、配准精度高、鲁棒性强等特点,为2种模式图像的融合奠定了基础.
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