[1]杨帆 谌海新 魏冬冬.基于GFCMA算法的医学彩色图像分割[J].计算机技术与发展,2007,(05):5-7.
 YANG Fan,CHEN Hai-xin,WEI Dong-dong.Medical Color Image Segmentation Based on Genetic Fuzzy C- Means Clustering Algorithm[J].,2007,(05):5-7.
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基于GFCMA算法的医学彩色图像分割()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2007年05期
页码:
5-7
栏目:
应用开发研究
出版日期:
1900-01-01

文章信息/Info

Title:
Medical Color Image Segmentation Based on Genetic Fuzzy C- Means Clustering Algorithm
文章编号:
1673-629X(2007)05-0005-03
作者:
杨帆 谌海新 魏冬冬
国防科学技术大学电子科学与工程学院
Author(s):
YANG FanCHEN Hai-xinWEI Dong-dong
Electronic Science and Engineering Institute,National University of Defense Techn
关键词:
医学彩色图像分割遗传算法模糊C-均值聚类
Keywords:
medical color images segmentation genetic algorithmfuzzy C-means clusteriring
分类号:
TN911.73
文献标志码:
A
摘要:
医学图像分割是医学图像分析的关键步骤,经典的模糊C-均值聚类算法(FCM)是常用方法,但其依赖于初始聚类中心的选择,通常存在局部收敛的缺陷。通过与遗传算法(GA)结合而成的遗传模糊C-均值聚类算法(GFCMA),采用RGB颜色空间,能够得到全局最优解,并在此基础上实现了医学彩色图像分割和特定目标提取,取得良好分割效果
Abstract:
Medical images segmentation is a critical step in medical image analysis. The classic fuzzy C- means clustering algorithm (FCM) is a commonly used method, but depends on the initial duster centers choice usually, which .means the presence of local de fects.Through GA, which combines genetic fuzzy C- means, clustering algorithm (GFCMA) using RGB color space to be a global optlmum And on tiffs basis it achieves a specific goal and medical color,images. The division achieves good results

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备注/Memo

备注/Memo:
杨帆(1976-),男,陕西岐山人,硕士研究生,研究方向为数字图像处理和模式识别;谌海新,博士,副教授,研究方向为图像图形与模式识别、人工智能、计算机仿真
更新日期/Last Update: 1900-01-01