计算机科学 ›› 2016, Vol. 43 ›› Issue (7): 290-293.doi: 10.11896/j.issn.1002-137X.2016.07.053
时永刚,谭继双,刘志文
SHI Yong-gang, TAN Ji-shuang and LIU Zhi-wen
摘要: 肾脏医学图像分割是医学图像分析和非侵入式计算机辅助诊断系统中的关键步骤。从CT、MRI图像中分割出肾脏及肾皮质,计算其体积和皮质厚度等信息,有助于评估肾脏的功能,从而制定相应的治疗方案。根据肾脏序列图像相邻切片之间结构灰度分布的相似性,提出了一种基于图割和水平集方法的自动肾脏及肾皮质分割方法。选取皮质区域具有足够对比度和清晰度的切片为初始参考图像,使用霍夫森林算法检测肾脏区域,对前景、背景进行均值聚类以估计其灰度分布,获取图割模型能量函数,分割出肾脏整体;通过形态学处理得到相邻切片肾脏的分割候选区域,重复上述分割。以此初步分割结果作为水平集方法的初始轮廓,进一步分割得到三维的肾脏整体和肾皮质区域。实验结果表明,基于图割和水平集的肾脏分割方法能够比较准确地分割出肾脏及肾皮质。
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