Fuzzy clustering of gradient‐echo functional MRI in the human visual cortex. Part I: Reproducibility

Reproducibility of human functional MRI (fMRI) studies is essential for clinical and neuroresearch applications of this new human brain mapping method. Based on a recently presented study on reproducibility of gradient‐echo fMRI in the human visual cortex (Moser et al. Magn Reson Imaging 1996; 14:567–579), comparing the performance of three different threshold strategies for correlation analysis, we demonstrate that (a) fuzzy clustering is a robust, model‐independent method to extract functional information in time and space; (b) intertrial reproducibility of cortical activation is significantly improved by the capability of fuzzy clustering to separate signal contributions from larger vessels, running perpendicular to the slice orientation, from activation apparently close to the primary visual cortex; and (c) for repeated single subject studies, SDs of <20% for signal enhancement in approximately 80% of the studies and SDs of <30% for activated area size in approximately 65% of the studies are obtained. This, however, depends also on signal‐to‐noise ratio, (motion) artifacts, and subject cooperation.

[1]  R. Turner,et al.  Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. , 1992, Proceedings of the National Academy of Sciences of the United States of America.

[2]  R Baumgartner,et al.  Fuzzy clustering of gradient‐echo functional MRI in the human visual cortex. Part II: Quantification , 1997, Journal of magnetic resonance imaging : JMRI.

[3]  Enrique H. Ruspini,et al.  Numerical methods for fuzzy clustering , 1970, Inf. Sci..

[4]  Jens Frahm,et al.  On the use of temporal correlation coefficients for magnetic resonance mapping of functional brain activation: Individualized thresholds and spatial response delineation , 1995, Int. J. Imaging Syst. Technol..

[5]  M Diemling,et al.  Quantification of signal changes in gradient recalled echo FMRI. , 1997, Magnetic resonance imaging.

[6]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[7]  J. Bezdek,et al.  FCM: The fuzzy c-means clustering algorithm , 1984 .

[8]  R Baumgartner,et al.  Quantification of intensity variations in functional MR images using rotated principal components. , 1996, Physics in medicine and biology.

[9]  J. Frahm,et al.  Functional MRI of human brain activation at high spatial resolution , 1993, Magnetic resonance in medicine.

[10]  J. R. Baker,et al.  Magnetic Resonance Imaging Mapping of Brain Function: Human Visual Cortex , 1992, Investigative radiology.

[11]  M Diemling,et al.  Modulation of signal changes in gradient-recalled echo functional MRI with increasing echo time correlate with model calculations. , 1997, Magnetic resonance imaging.

[12]  M Diemling,et al.  Reproducibility and postprocessing of gradient-echo functional MRI to improve localization of brain activity in the human visual cortex. , 1996, Magnetic resonance imaging.

[13]  P. Bandettini,et al.  Synthetic images by subspace transforms. I. Principal components images and related filters. , 1994, Medical physics.

[14]  J. Mansfield,et al.  Noninvasive Assessment of Regional and Temporal Variations in Tissue Oxygenation by Near-Infrared Spectroscopy and Imaging , 1997 .

[15]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[16]  Donald Gustafson,et al.  Fuzzy clustering with a fuzzy covariance matrix , 1978, 1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes.

[17]  S. Ogawa,et al.  Oxygenation‐sensitive contrast in magnetic resonance image of rodent brain at high magnetic fields , 1990, Magnetic resonance in medicine.

[18]  E C Wong,et al.  Processing strategies for time‐course data sets in functional mri of the human brain , 1993, Magnetic resonance in medicine.

[19]  J. C. Dunn,et al.  A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters , 1973 .