| 基于发作间期颅内脑电高频振荡的癫痫病灶定位 | |
| 郑霄 ; 张丹 ; 石岩芳 ; 周文静 ; 洪波 ; ZHENG Xiao ; ZHANG Dan ; SHI Yanfang ; ZHOU Wenjing ; HONG Bo | |
| 2016-03-30 ; 2016-03-30 | |
| 关键词 | 颅内脑电 高频振荡 非参数模型 致痫灶 osteoarthritis early screening infrared thermography automatic diagnosis R742.1 |
| 其他题名 | Epileptogenic zone localization based on intracranial interictal high frequency oscillations |
| 中文摘要 | 目的通过癫痫发作间期高频颅内脑电信号的记录和分析,实现一种基于概率模型的癫痫病灶定位自动算法。方法以一段时间内颅内脑电高频能量的整体波动性水平为指标,建立大数据概率模型以判断某电极是否覆盖致痫灶。结果本文分析了来自12例癫痫患者948个颅内电极的癫痫发作间期颅内脑电数据,与医生人工定位结果作对比,平均敏感性80.4%±17.3%,特异性87.7%±17.2%;模型的稳定性和性能随着数据量增加而提高。结论本文所提出高频能量波动性算法基于概率模型,不依赖个体化参数、自动化程度高、性能好,有良好的临床应用前景。; Objective To propose and implement an automatic method based on a probability model using intracranially recorded high-frequency brain activity for the identification of epileptogenic zone.Methods Big data probability mode】was constructed based on the characteristics of the epileptogenic activities described by the degree of overall high-frequency power fluctuation in order to identify whether a channel was located in epileptogenic zone or not.Results By using the probability model with 948-electrode data from 12 patients,and compared with the results marked by neurologists,80.4%± 17.3%sensitivity and 87.7%± 17.2%specificity were achieved.Conclusions Based on probability model,the proposed method does not rely on individual parameters,and possesses high degree of automation,good performance and a bright perspective in clinical diagnosis. |
| 语种 | 中文 ; 中文 |
| 内容类型 | 期刊论文 |
| 源URL | [http://ir.lib.tsinghua.edu.cn/ir/item.do?handle=123456789/147461]  |
| 专题 | 清华大学 |
| 推荐引用方式 GB/T 7714 | 郑霄,张丹,石岩芳,等. 基于发作间期颅内脑电高频振荡的癫痫病灶定位[J],2016, 2016. |
| APA | 郑霄.,张丹.,石岩芳.,周文静.,洪波.,...&HONG Bo.(2016).基于发作间期颅内脑电高频振荡的癫痫病灶定位.. |
| MLA | 郑霄,et al."基于发作间期颅内脑电高频振荡的癫痫病灶定位".(2016). |
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