首页> 外文会议>IEEE International Conference on BioInformatics and BioEngineering >Segmentation of Brain MR Images Using an Ant Colony Optimization Algorithm
【24h】

Segmentation of Brain MR Images Using an Ant Colony Optimization Algorithm

机译:使用蚁群优化算法进行脑MR图像的分割

获取原文

摘要

In this paper, we describe a segmentation method for brain MR images using an ant colony optimization (ACO) algorithm. This is a relatively new meta-heuristic algorithm and a successful paradigm of all the algorithms which take advantage of the insectpsilas behavior. It has been applied to solve many optimization problems with good discretion, parallel, robustness and positive feedback. As an advanced optimization algorithm, only recently, researchers began to apply ACO to image processing tasks. Hence, we segment the MR brain image using ant colony optimization algorithm. Compared to traditional meta-heuristic segmentation methods, the proposed method has advantages that it can effectively segment the fine details.
机译:在本文中,我们描述了使用蚁群优化(ACO)算法的脑MR图像的分段方法。这是一种相对较新的元启发式算法和成功的所有算法的范例,利用虫害行为。它已被应用于解决许多优化问题,良好的自由裁量权,平行,鲁棒性和正反馈。作为一个先进的优化算法,最近,研究人员开始将ACO应用于图像处理任务。因此,我们使用蚁群优化算法分段MR脑图像。与传统的元启发式分割方法相比,所提出的方法具有优势,它可以有效地分段细节。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号