计算机应用

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一种新的基于区域竞争模型的水平集医学图像分割方法

陈湘文 赵卫东 李吉超   

  1. 企业数字化技术教育部工程研究中心;同济大学CAD研究中心 企业数字化技术教育部工程研究中心;同济大学 CAD研究中心
  • 收稿日期:2007-11-05 修回日期:2007-12-12 发布日期:2008-04-01 出版日期:2008-04-01
  • 通讯作者: 陈湘文

Novel level set approach for medical image segmentation based on region competition model

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  • Received:2007-11-05 Revised:2007-12-12 Online:2008-04-01 Published:2008-04-01
  • Contact: Xiang-Wen Chen

摘要: 传统的基于梯度模型的水平集分割方法在水平集曲线演化过程中存在着边界泄漏问题。针对这个问题,提出了一种基于改进区域竞争模型的水平集分割方法。本方法首先通过概率分布公式计算出水平集曲线属于目标区域和背景区域的概率;其次,将概率差值连同权重因子添加到水平集函数方程中,使曲线在演化过程中能量函数达到最小;最终,利用图像的区域信息提高水平集曲线识别边界的能力。实验结果表明该方法能够很好地实现医学图像的分割。

关键词: 区域竞争, 水平集方法, 医学图像分割, 边界泄露

Abstract: Traditional level set method based on gradient model has the leaking problem during the curve evolution. A level set method based on region competition model was proposed to solve this problem. Firstly, the probabilities of the level set curve that belonged to the object region and background region were calculated respectively using probability distribution equation; Secondly, the difference of the foreground and background probabilities and weights were added to the level set function to minimize the energy function during the curve evolution; Finally, the images regional information could be used to identify the object boundary. Experimental results show that the proposed method can segment the medical image well.

Key words: region competition, level set method, medical image segmentation, boundary leakage