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一种用于侧脑室分割的两步活动轮廓模型算法
引用本文:高鸿姝,冯成德,张慧.一种用于侧脑室分割的两步活动轮廓模型算法[J].中国测试技术,2006,32(6):55-57,116.
作者姓名:高鸿姝  冯成德  张慧
作者单位:1. 四川大学制造学院,四川,成都,610065
2. 四川电力职业技术学院基础部,四川,成都,610072
摘    要:基于活动轮廓模型的分割广泛应用于医学图像,提出了一种两步活动轮廓模型算法用于核磁共振脑部图像中侧脑室的分割。首先用传统活动轮廓模型求解,然后采用遗传算法进行优化,得到了较好的结果,解决了一般活动轮廓模型对侧脑室的尖锐角点处分割效果不理想的问题。

关 键 词:角点  活动轮廓模型  遗传算法  蛇模型  侧脑室
文章编号:1672-4984(2006)06-0055-03
收稿时间:2006-06-03
修稿时间:2006-06-032006-08-15

A two-step active contour model-based algorithm for lateral ventricles segmentation in MRI
GAO Hong-shu,FENG Cheng-de,ZHANG Hui.A two-step active contour model-based algorithm for lateral ventricles segmentation in MRI[J].China Measurement Technology,2006,32(6):55-57,116.
Authors:GAO Hong-shu  FENG Cheng-de  ZHANG Hui
Affiliation:1.Department of Manufacturing Science and Engineefing,Sichuan University,Chengdu 610065,China; 2.Basic Department, Sichuan Electric Technology College, Chengdu 610072, China
Abstract:Active model-based segmentation has frequently been used in medical image processing. The author introduces a new two-step active model-based algorithm for lateral ventricles segmentation in MRI. It uses traditional snake model for segmentation in the first step, then uses genetic algorithm to optimize. The approach is advanced for segmentation in sharp angular point, and experimental result is satisfied.
Keywords:Angular point  Active contour model  Genetic algorithm  Snake model  Lateral ventricle
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