1. 国防科技大学机电工程与自动化学院自动控制系,湖南,长沙,410073
2. 中南大学湘雅医学院生理教研室,湖南,长沙,410008
3. 国防科技大学机电工程与自动化学院自动控制系湖南长沙,410073
4. 中南大学湘雅医学院生理教研室湖南长沙,410008
纸质出版:2007
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王玉成, 胡德文, 刘亚东, 等. 基于频谱特征的脑皮层动静脉分离[J]. 电子学报, 2007,35(1):44-48.
WANG Yu-cheng, HU De-wen, LIU Ya-dong, et al. Separation of Artery and Vena in Cerebral Cortex Based on Spectrum Features[J]. Acta Electronica Sinica, 2007, 35(1): 44-48.
光学功能成像是一种基于内源信号的功能映射方法
成像系统所采集到的脑皮层图像序列含有丰富的生理信号.本文利用心跳和呼吸引起的振荡信号的谱值特征实现了动静脉的分离.文中首先采用阈值分割和区域增长的方法对脑皮层的血管网络进行了提取
然后根据动脉波动信号频率分布在5~6 Hz之间而静脉波动信号频率分布在1~2 Hz之间的生理特征
分别计算其谱值
依据各信号谱值在特定频谱段内所占的功率谱百分比的不同实现了动脉和静脉的分离.最后
本文讨论了动、静脉中脉搏、呼吸以及0.1 Hz频谱分量的谱值和相位对动静脉分离的影响和潜在利用价值.
Optical Imaging(OI) is a functional imaging technique based on intrinsic signals which contain abundant physiological sources.In this paper
we tried to separate artery from vena based on spectrum features of the heartbeat and respiration oscillations.Vessel network was firstly extracted from a frame of cortical image by threshold segmentation and region growing method
then we computed the spectral powers of heartbeat and respiration signals separately according to an oscillation-related physiological feature that arterial oscillation distributes between 5 Hz and 6 Hz and venous oscillation distributes between 1 Hz and 2 Hz.Separation of artery and vena was successfully achieved by utilizing the spectral power-percentage of heartbeat and respiration signals.The potential value of 0.1Hz oscillation in artery and vena separation was discussed at last.
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