Comparison of filtering methods for fMRI datasets

被引:48
作者
Kruggel, F [1 ]
von Cramon, DY [1 ]
Descombes, X [1 ]
机构
[1] Max Planck Inst Cognit Neurosci, D-04103 Leipzig, Germany
关键词
flMRI; spatio-temporal filtering; physiological noise; preprocessing;
D O I
10.1006/nimg.1999.0490
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
When studying complex cognitive tasks using functional magnetic resonance imaging (fMRI) one often encounters weak signal responses. These weak responses are corrupted by noise and artifacts of various sources. Preprocessing of the raw data before the application of test statistics helps to extract the signal and can vastly improve signal detection. Artifact sources and algorithms to handle them are discussed. In an empirical approach targeted to yield an optimal recovery of the hemodynamic response, we implemented a test bed for baseline correction and noise-filtering methods. A known signal is modulated onto foreground patches obtained from event-related fMRI experiments. Quantitative performance measures are defined to optimize the characteristics of a given filter and to compare their results. Marked improvements in the sensitivity and selectivity are achieved by optimized filtering. Examples using real data underline the usefulness of this preprocessing sequence. (C) 1999 Academic Press.
引用
收藏
页码:530 / 543
页数:14
相关论文
共 33 条
[1]   Functional MRI of brain activation induced by scanner acoustic noise [J].
Bandettini, PA ;
Jesmanowicz, A ;
Van Kylen, J ;
Birn, RM ;
Hyde, JS .
MAGNETIC RESONANCE IN MEDICINE, 1998, 39 (03) :410-416
[2]  
Benali H, 1997, LECT NOTES COMPUT SC, V1230, P285
[3]   Bayesian image classification using Markov random fields [J].
Berthod, M ;
Kato, Z ;
Yu, S ;
Zerubia, J .
IMAGE AND VISION COMPUTING, 1996, 14 (04) :285-295
[4]   Magnetic field changes in the human brain due to swallowing or speaking [J].
Birn, RM ;
Bandettini, PA ;
Cox, RW ;
Jesmanowicz, A ;
Shaker, R .
MAGNETIC RESONANCE IN MEDICINE, 1998, 40 (01) :55-60
[5]   Reduction of physiological fluctuations in fMRI using digital filters [J].
Biswal, B ;
DeYoe, EA ;
Hyde, JS .
MAGNETIC RESONANCE IN MEDICINE, 1996, 35 (01) :107-113
[6]  
BISWAL B, 1994, P SMR 2 ANN M SAN FR, P653
[7]   Statistical methods of estimation and inference for functional MR image analysis [J].
Bullmore, E ;
Brammer, M ;
Williams, SCR ;
Rabehesketh, S ;
Janot, N ;
David, A ;
Mellers, J ;
Howard, R ;
Sham, P .
MAGNETIC RESONANCE IN MEDICINE, 1996, 35 (02) :261-277
[8]   Noise suppression digital filter for functional magnetic resonance imaging based on image reference data [J].
Buonocore, MH ;
Maddock, RJ .
MAGNETIC RESONANCE IN MEDICINE, 1997, 38 (03) :456-469
[9]   fMRI study of face perception and memory using random stimulus sequences [J].
Clark, VP ;
Maisog, JM ;
Haxby, JV .
JOURNAL OF NEUROPHYSIOLOGY, 1998, 79 (06) :3257-3265
[10]   Parametric analysis of fMRI data using linear systems methods [J].
Cohen, MS .
NEUROIMAGE, 1997, 6 (02) :93-103