基于数学形态学的功能磁共振信号漂移校正方法

Drift correction in fMRI signal based on mathematical morphology

目的探讨基于数学形态学的功能磁共振信号漂移校正新方法。方法根据fMRI信号漂移成分的形态特征,采用基于数学形态学的方法校正fMRI信号的基线漂移。结果应用模拟数据和真实数据测试表明,数学形态学方法能够有效地校正fMRI信号的基线漂移。结论本研究提出的方法能够同时校正线性和非线性漂移,而不需要任何统计学模型假设。

Objective To establish a new approach based on mathematical morphology that can effectively reduce the drifts in functional magnetic resonance imaging （fMRI） signals. Methods Based on investigation of the characteristic of drifted fMRI signals, a mathematical morphology method for baseline drift correction was presented. Results With both simulated data and real fMRI data, the results of the experiment showed that the mathematical morphology method can effectively correct the baseline drifts. Conclusion Both linear and nonlinear drifts can be removed with the proposed method without any statistical model assumption.