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Systems and methods for estimating and removing magnetic resonance imaging gradient field-induced voltages from electrophysiology signals

机译:从电生理信号估计和去除磁共振成像梯度场感应电压的系统和方法

摘要

Systems and methods for estimating time-dependent voltages that are induced in electrophysiological monitoring systems by magnetic field gradients generated during a magnetic resonance imaging (“MRI”) scan are provided. The gradient-induced voltages are subsequently removed from signals acquired with the electrophysiological monitoring system during an MRI scan. As an example, the electrophysiological monitoring system can include an electrocardiography (“ECG”) system, an electroencephalography (“EEG”) system, an electromyography (“EMG”) system, a voltage device tracking (“VDT”) system, and so on. The gradient-induced voltages are estimated using a two-step procedure in which a learning algorithm is used to determine fitting parameters to be used in a model of the gradient-induced voltages. The fitting parameters are then used together with the model to extract the gradient-induced voltages from signals acquired during an MRI scan. The gradient-induced voltages can then be removed from the acquired signals.
机译:提供了用于估计由在磁共振成像(“ MRI”)扫描期间产生的磁场梯度在电生理监测系统中感应的随时间变化的电压的系统和方法。随后,在MRI扫描期间,将梯度感应电压从电生理监测系统采集的信号中去除。作为示例,电生理监测系统可以包括心电图(“ ECG”)系统,脑电图(“ EEG”)系统,肌电图(“ EMG”)系统,电压设备跟踪(“ VDT”)系统等等。上。使用两步过程估算梯度感应电压,其中使用学习算法来确定要在梯度感应电压模型中使用的拟合参数。然后将拟合参数与模型一起使用,以从MRI扫描期间获取的信号中提取梯度感应电压。然后可以从所采集的信号中去除梯度感应电压。

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