摘要
目的采用电阻抗成像技术重建三维头部模型的阻抗分布图像,检测组织是否发生病变。方法在有限元球头模型和真实头部模型两种三维组织模型上进行仿真,采用微分进化算法重构组织图像,有效定位阻抗突变区域,检测病变组织部位。结果该算法能够精确重建组织图像,成功检测病变区域。结论本法是一种简单、鲁棒性强的进化类全局优化算法,用于电阻抗成像技术中,进化总能得到很好收敛,成像质量较高,可靠性较强。
Objective To reconstruct the real conductivity images of 3D head model, and to detect brain lesion by means of electrical impedance tomography (EIT) technology. Methods In order to locate the pathological changes of head impedance effectively, a series of computer simulation were conducted on a finite element model and a realistic-geometry head model, and differential evolution algorithm was adopted to reconstruct the conductivity image of the head tissue. Results The proposed algorithm could accurately reconstruct the impedance of the head tissue and successfully detect lesion area presently. Conclusion The global optimization and evolution algorithm can be applied to EIT simply with good convergent and robustness. The reconstructed images show higher quality and are reliable.
出处
《中国医学影像技术》
CSCD
北大核心
2014年第7期1113-1116,共4页
Chinese Journal of Medical Imaging Technology
基金
国家自然科学基金青年基金项目(NSFC-51107130)
关键词
电阻抗成像
脑疾病
有限元分析
微分进化
Electrical impedance tomography
Brain diseases
Finite element analysis
Differential evolution