脑磁源定位重建算法研究进展
Research Progress in Brain Magnetic Source Localization Reconstruction Algorithm
羊艳玲 1姚旭峰 2罗世昌 1时承 1高秀敏 3吴韬2
作者信息
- 1. 上海理工大学健康科学与工程学院,上海 200093;上海健康医学院医学影像学院,上海 201318
- 2. 上海健康医学院医学影像学院,上海 201318
- 3. 上海理工大学光电信息与计算机工程学院,上海 200093
- 折叠
摘要
脑磁图作为一种非侵入性大脑功能神经成像方法,以其高时间分辨率和无创性等特点得到临床的广泛关注.脑磁源定位研究的核心问题是利用脑外磁场数据(脑磁图)来推断脑内电流源的分布,并进一步确定神经源的位置和活动模式,这一逆问题的求解过程存在不唯一性和不适定性的难题.脑磁源定位重建方法分为分布源模型和偶极子定位.综述脑磁图和磁源成像的发展过程和研究进展,分布源模型包括最小范数估计法、低分辨率脑电磁断层扫描、欠定系统局域解法、贝叶斯推断估计法、波束成形器和稀疏源成像等;偶极子定位包括最大熵方法、最小二乘范数、多信号分类算法、神经网络和遗传算法等;论述各类算法的特色、局限性及其存在的问题;随着技术的不断进步,融合多种脑功能技术的多模态重建方法有望成为神经功能诊断领域的主导性检测技术.
Abstract
As a non-invasive functional neuroimaging method of human brain,magnetoencephalography has been widely concerned in clinical applications due to its high temporal resolution and non-invasive characteristics.The inverse problem of inferring the distribution of current sources in the brain from the data of scalp magnetic field is the central problem in the research of brain magnetic source localization.The difficulty lies in the uniqueness and ill-posed feature of the inverse problem.The reconstruction methods are divided into two categories:distributed source model and dipole localization.Therefore,this article systematically discussed the development of magnetoencephalography and magnetic source imaging.The distributed source model includes minimum norm estimation,low resolution brain electromagnetic tomography,focal underdetermined system solution,Bayesian estimation,beamformer and sparse source imaging.Dipole localization includes maximum entropy method,least-squares minimum norm,multiple-signal classification algorithm,neural network and genetic algorithm.Existing problems and development trends were analyzed,highlighting that multimodal reconstruction methods that integrate multiple brain function technologies are expected to become the most important detection technology for neural function diagnosis.
关键词
脑磁图/磁源定位重建/逆问题/分布源模型/偶极子定位Key words
magnetoencephalography/magnetic source localization reconstruction/inverse problem/distributed source model/dipole localization引用本文复制引用
基金项目
国家重点研发计划(2020YFC2008700)
国家自然科学基金(61971275)
国家自然科学基金(81830052)
上海市科学技术委员会地方院校能力建设项目(23010502700)
出版年
2024
NETL
NSTL
万方数据