冠状动脉造影过程中,由于人体骨骼、肌肉、器官等组织对X射线吸收程度不同,得到的冠状动脉造影图像亮度不均匀,传统的区域生长算法无法准确分割不均匀亮度的图像,而且种子点的选取需要人工交互,效率低下.针对这些问题,提出了一种改进区域生长算法,该算法自动生成一组种子点,种子点生长时,使用生长区域的局部平均值作为生长准则中的参数,最后使用医学影像计算与计算机辅助介入(MEdICAl IMAgE COMPuTIng And COMPuTEr ASSISTEd InTErVEnTIOn,MICCAI)准则对分割后的图像进行评价.实验表明,使用该算法对冠状动脉造影图像进行分割,能得到较好的结果,且不需要人工交互,提高了图像分割的效率和准确性.The intensity of coronary artery angiograms is non-uniform since different organizations,such as the bones,muscles,and organs,have different absorption of X-ray during angiography.The classical region growing algorithm has poor effect on these non-uniform intensity images,and it is also inefficient since the seeds must select manually.An improved region growing algorithm is presented by this paper,which not only produce seeds automatically,but also use a local parameter in growing criteria.Then we used Miccai criteria to evaluate the result of our algorithm.The efficacy of the approach is demonstrated with experiments.国家自然科学基金项目(61102137;60971085); 福建省自然科学基金项目(2011J01366;2010J01350
