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基于水平集方法的图像分割
  • 期刊名称:医学影像学杂志。2007.8, 17(8): 864-867.
  • 时间:0
  • 分类:R445.2[医药卫生—影像医学与核医学;医药卫生—诊断学;医药卫生—临床医学] R811[医药卫生—放射医学;医药卫生—临床医学]
  • 作者机构:[1]哈尔滨工业大学Bio-X中心,黑龙江哈尔滨150001
  • 相关基金:本课题得到国家自然科学基金(60575016)资助
  • 相关项目:基于脑图谱与图象配准的T2权值MR图像自动标注研究
中文摘要:

目的:提取T1加权MR脑图像中的侧脑室。方法:首先用高斯滤波对原始图像进行平滑,然后利用改进的FastMarching方法对脑图像进行分割。根据T1加权MR脑图像的成像特点并结合区域信息重新定义了Fast Marching方法的速度函数,该速度函数具有良好的抗泄漏能力。结果:对一系列T1加权MR脑图像进行了分割实验,成功提取出了侧脑室。结论:改善了传统Fast Marching方法在弱边界处易泄漏的缺陷,具有更好的分割效果。

英文摘要:

Objective:To segment the cerebral lateral ventricle from T1-weighted MR images. Methods:Firstly, the MR images are smoothed by Gaussian filter, and then segmented with improved Fast Marching method. With the help of region information and the characteristies of T1-weighted MR images, a new speed function for Fast marching method was proposed. The new speed function has a higher evolutive velocity in the objective area while it has a slower evolutive velocity rear the objective region edges.Results:In the experiments, the lateral ventricles from a series of T1-weighted MR images were partitioned successful. Conclusion:The results proved that the proposed algorithm gets better outcomes than the common Fast Marching method especially when the MR images have weak edges.

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