赖昀,孙兵,丁肇华,王加俊.改进型遗传算法在脑白质纤维追踪成像中的应用[J].中国医学影像技术,2012,28(10):1922~1926
改进型遗传算法在脑白质纤维追踪成像中的应用
Application of improved genetic algorithm for white matter tractography
投稿时间:2012-05-22  修订日期:2012-07-01
DOI:
中文关键词:  脑白质  扩散张量成像  遗传算法  模拟退火算法
英文关键词:White matter  Diffusion tensor imaging  Genetic algorithm  Simulated annealing algorithm
基金项目:国家自然科学基金(60871086)。
作者单位E-mail
赖昀 苏州大学电子信息学院, 江苏 苏州 215006  
孙兵 苏州大学电子信息学院, 江苏 苏州 215006 sunbing@suda.edu.cn 
丁肇华 范德堡大学成像科学研究所, 美国 田纳西州 37232-2310  
王加俊 苏州大学电子信息学院, 江苏 苏州 215006  
摘要点击次数: 2453
全文下载次数: 1065
中文摘要:
      目的 针对基本遗传纤维追踪算法易早熟等缺点,提出结合遗传算法(GA)、模拟退火算法(SA)的脑白质纤维可视化方法。方法 在遗传进化的初期,依据适应值,按照轮盘赌选择规则选择纤维,在GA接近收敛的中期引入SA作为繁殖算子,并以一定交叉概率和变异概率调整纤维,获得较优纤维路径。结果 改进后的算法追踪的纤维能量更小,且更加符合扩散张量场的分布。结论 遗传模拟退火纤维追踪算法能够克服传统GA易早熟及易陷入局部最优解的缺点,可实现脑白质纤维的三维可视化。
英文摘要:
      Objective To present a new method combining the genetic algorithm (GA) and simulated annealing algorithm (SA) for 3D visualization of fiber bundles based on the weakness of prematurity of genetic white matter fiber tractography. Methods The roulette wheel selection was used for selecting fibers according to fitness in the early stages of GA. Then in the middle stage of GA, SA was introduced for breeding operator of basic GA, and fiber paths between regions of interest were adjusted to find better fibers at certain crossover probability and mutation probability. Results Compared with basic GA tractography, the improved algorithm could find fibers with smaller energy and more in line with the tensor field’s distribution. Conclusion The genetic simulated annealing algorithm overcomes the weakness such as prematurity and convergence to the local optimum solution, therefore can realize 3D visualization of white matter fibers.
查看全文  查看/发表评论  下载PDF阅读器