Contrast‐to‐noise ratio (CNR) as a quality parameter in fMRI

To evaluate the impact of data quality on the localization of brain activation in functional magnetic resonance imaging (fMRI) and to explore whether the temporal contrast‐to‐noise‐ratio (CNR) provides a quantitative parameter to estimate fMRI quality.

[1]  Rupert Lanzenberger,et al.  FMRI reveals functional cortex in a case of inconclusive Wada testing , 2005, Clinical Neurology and Neurosurgery.

[2]  G. Glover,et al.  Neuroimaging at 1.5 T and 3.0 T: Comparison of oxygenation‐sensitive magnetic resonance imaging , 2001, Magnetic resonance in medicine.

[3]  K. Thulborn,et al.  Clinical rationale for very-high-field (3.0 Tesla) functional magnetic resonance imaging. , 1999, Topics in magnetic resonance imaging : TMRI.

[4]  Todd B. Parrish,et al.  Impact of signal‐to‐noise on functional MRI , 2000 .

[5]  Gaohong Wu,et al.  Theoretical noise model for oxygenation‐sensitive magnetic resonance imaging , 2005, Magnetic resonance in medicine.

[6]  Amir Reza Tahamtan,et al.  Evaluation of preoperative high magnetic field motor functional MRI (3 Tesla) in glioma patients by navigated electrocortical stimulation and postoperative outcome , 2005, Journal of Neurology, Neurosurgery & Psychiatry.

[7]  Rupert Lanzenberger,et al.  Influence of fMRI smoothing procedures on replicability of fine scale motor localization , 2005, NeuroImage.

[8]  C. Windischberger,et al.  Quantification in functional magnetic resonance imaging: fuzzy clustering vs. correlation analysis. , 1998, Magnetic resonance imaging.

[9]  R. Buxton,et al.  Detection Power, Estimation Efficiency, and Predictability in Event-Related fMRI , 2001, NeuroImage.

[10]  Lawrence L. Wald,et al.  Comparison of physiological noise at 1.5 T, 3 T and 7 T and optimization of fMRI acquisition parameters , 2005, NeuroImage.

[11]  K Willmes,et al.  Activation in primary and secondary motor areas in patients with CNS neoplasms and weakness , 2002, Neurology.

[12]  F. A. Seiler,et al.  Numerical Recipes in C: The Art of Scientific Computing , 1989 .

[13]  C Windischberger,et al.  Improvement of presurgical patient evaluation by generation of functional magnetic resonance risk maps , 2000, Neuroscience Letters.

[14]  Mark D'Esposito,et al.  Variation of BOLD hemodynamic responses across subjects and brain regions and their effects on statistical analyses , 2004, NeuroImage.

[15]  John C. Gore,et al.  ROC Analysis of Statistical Methods Used in Functional MRI: Individual Subjects , 1999, NeuroImage.

[16]  K Willmes,et al.  Functional MRI for presurgical planning: problems, artefacts, and solution strategies , 2001, Journal of neurology, neurosurgery, and psychiatry.

[17]  Kurt Hornik,et al.  A quantitative comparison of functional MRI cluster analysis , 2004, Artif. Intell. Medicine.

[18]  G. Glover,et al.  Physiological noise in oxygenation‐sensitive magnetic resonance imaging , 2001, Magnetic resonance in medicine.

[19]  C Windischberger,et al.  Quantification of fMRI artifact reduction by a novel plaster cast head holder , 2000, Human brain mapping.