The work of this paper analyzes the performance of Sensitivity Encoding (SENSE) through actual data sets and determines the problem of computational efficiency. It corrects the error of the detection signal through th...The work of this paper analyzes the performance of Sensitivity Encoding (SENSE) through actual data sets and determines the problem of computational efficiency. It corrects the error of the detection signal through the calibration function of the percentage signal change, and uses the three-dimensional sensor image reconstruction technology to calibrate the sensitivity of the blood to the magnetic change, enhances the sensitivity of the magnetic susceptibility gradient, and reduces the scanning time of the MRI experiment. The actual data set handles the image resolution. The performance and experimental results of SENSE are analyzed through actual data sets.展开更多
Blood oxygenation level dependence signal (BOLD) for functional magnetic resonance imaging (FMRI), is the use of blood magnetization depending on the oxygenation state of hemoglobin. Susceptibility gradient can shift ...Blood oxygenation level dependence signal (BOLD) for functional magnetic resonance imaging (FMRI), is the use of blood magnetization depending on the oxygenation state of hemoglobin. Susceptibility gradient can shift and skew k-space trajectories and it leads to echo time shift and BOLD sensitivity change. FMRI can be used to detect the signal, the change of the susceptibility gradient of the signal and the distortion of k space trajectory, resulting in echo time shift and BOLD sensitivity change. Using the percentage signal change (PSC) and calibration function, it can be applied to many different fields, such as age-related research. In this paper, the performance of BOLD signal change correction based on sensitivity gradient was verified by real data group calculation, and methods of further improving the calculation speed were analyzed. This paper also analyzed the performance of correcting the variations of BOLD Signal due to susceptibility gradients with real data set, and identified the computational issues that need to be improved for further research.展开更多
This paper introduces a stochastic hemodynamic system to describe the brain neural activity based on the balloon model. A continuous-discrete extended Kalman filter is used to estimate the nonlinear model states. The ...This paper introduces a stochastic hemodynamic system to describe the brain neural activity based on the balloon model. A continuous-discrete extended Kalman filter is used to estimate the nonlinear model states. The stability, controllability and observability of the proposed model are described based on the simulation and measurement data analysis. The observability and controllability characteristics are in- troduced as significant factors to validate the preference of different hemodynamic factors to be considered for diagnosis and monitoring in clinical applications. This model also can be efficiently applied in any monitoring and control platform include brain and for study of hemodynamics in brain imaging modalities such as pulse oximetry and functional near infrared spectroscopy. The work is on progress to extend the proposed model to cover more hemodynamic and neural brain signals for real-time in-vivo application.展开更多
A new technique is proposed in this paper for real-time monitoring of brain neural activity based on the balloon model. A continuous-discrete extended Kalman filter is used to estimate the nonlinear model states. The ...A new technique is proposed in this paper for real-time monitoring of brain neural activity based on the balloon model. A continuous-discrete extended Kalman filter is used to estimate the nonlinear model states. The stability, controlla- bility and observability of the proposed model are described based on the simulation and measured clinical data analysis. By introducing the controllable and observable states of the hemodynamic signal we have developed a numerical tech- nique to validate and compare the impact of brain signal parameters affecting on BOLD signal variation. This model increases significantly the signal-to-noise-ratio (SNR) and the speed of brain signal processing. A linear-quadratic regulator (LQR) also has been introduced for optimal control of the model.展开更多
利用功能磁共振成像(fMRI)进行脑功能研究是目前的一个热点,本文以逻辑计算为认知任务,利用fMRI进行数据采集,通过SPM软件分析得到激活脑区,提取感兴趣区(Regions of interest,ROI)的平均BOLD信号(Average-BOLD),并利用主成分分析(Princ...利用功能磁共振成像(fMRI)进行脑功能研究是目前的一个热点,本文以逻辑计算为认知任务,利用fMRI进行数据采集,通过SPM软件分析得到激活脑区,提取感兴趣区(Regions of interest,ROI)的平均BOLD信号(Average-BOLD),并利用主成分分析(Principal component analysis,PCA)方法提取ROI内BOLD信号(PCA-BOLD),通过Average-BOLD、PCA-BOLD信号与实验设计的逻辑任务曲线进行比较,认为PCA-BOLD信号可以更好的作为fMRI激活脑区的定量评估指标,用来衡量ROI激活强度,并进行脑功能基础研究。展开更多
文摘The work of this paper analyzes the performance of Sensitivity Encoding (SENSE) through actual data sets and determines the problem of computational efficiency. It corrects the error of the detection signal through the calibration function of the percentage signal change, and uses the three-dimensional sensor image reconstruction technology to calibrate the sensitivity of the blood to the magnetic change, enhances the sensitivity of the magnetic susceptibility gradient, and reduces the scanning time of the MRI experiment. The actual data set handles the image resolution. The performance and experimental results of SENSE are analyzed through actual data sets.
文摘Blood oxygenation level dependence signal (BOLD) for functional magnetic resonance imaging (FMRI), is the use of blood magnetization depending on the oxygenation state of hemoglobin. Susceptibility gradient can shift and skew k-space trajectories and it leads to echo time shift and BOLD sensitivity change. FMRI can be used to detect the signal, the change of the susceptibility gradient of the signal and the distortion of k space trajectory, resulting in echo time shift and BOLD sensitivity change. Using the percentage signal change (PSC) and calibration function, it can be applied to many different fields, such as age-related research. In this paper, the performance of BOLD signal change correction based on sensitivity gradient was verified by real data group calculation, and methods of further improving the calculation speed were analyzed. This paper also analyzed the performance of correcting the variations of BOLD Signal due to susceptibility gradients with real data set, and identified the computational issues that need to be improved for further research.
文摘This paper introduces a stochastic hemodynamic system to describe the brain neural activity based on the balloon model. A continuous-discrete extended Kalman filter is used to estimate the nonlinear model states. The stability, controllability and observability of the proposed model are described based on the simulation and measurement data analysis. The observability and controllability characteristics are in- troduced as significant factors to validate the preference of different hemodynamic factors to be considered for diagnosis and monitoring in clinical applications. This model also can be efficiently applied in any monitoring and control platform include brain and for study of hemodynamics in brain imaging modalities such as pulse oximetry and functional near infrared spectroscopy. The work is on progress to extend the proposed model to cover more hemodynamic and neural brain signals for real-time in-vivo application.
文摘A new technique is proposed in this paper for real-time monitoring of brain neural activity based on the balloon model. A continuous-discrete extended Kalman filter is used to estimate the nonlinear model states. The stability, controlla- bility and observability of the proposed model are described based on the simulation and measured clinical data analysis. By introducing the controllable and observable states of the hemodynamic signal we have developed a numerical tech- nique to validate and compare the impact of brain signal parameters affecting on BOLD signal variation. This model increases significantly the signal-to-noise-ratio (SNR) and the speed of brain signal processing. A linear-quadratic regulator (LQR) also has been introduced for optimal control of the model.
文摘利用功能磁共振成像(fMRI)进行脑功能研究是目前的一个热点,本文以逻辑计算为认知任务,利用fMRI进行数据采集,通过SPM软件分析得到激活脑区,提取感兴趣区(Regions of interest,ROI)的平均BOLD信号(Average-BOLD),并利用主成分分析(Principal component analysis,PCA)方法提取ROI内BOLD信号(PCA-BOLD),通过Average-BOLD、PCA-BOLD信号与实验设计的逻辑任务曲线进行比较,认为PCA-BOLD信号可以更好的作为fMRI激活脑区的定量评估指标,用来衡量ROI激活强度,并进行脑功能基础研究。
