A hierarchical clustering method for analyzing functional MR images.

We introduce a novel method for detecting anatomic and functional structures in fMRI. The main idea is to divide the data hierarchically into smaller groups using k-means clustering. The separation is halted if the clusters contain no further structure that is verified by several independent tests. The resulting cluster centers are then used for computing the final results in one step. The procedure is flexible, fast to compute, and the numbers of clusters in the data are obtained in a data-driven manner. Applying the algorithm to synthetic fMRI data yields perfect separation of "anatomic," i.e., time-invariant, and "functional," i.e., time-varying, information for a standard off-on paradigm and a typical functional contrast-to-noise ratio of two and higher. In addition, an EPI-fMRI data set of the human motor cortex was analyzed to demonstrate the performance of this novel approach in vivo.

[1]  J. A. Hartigan,et al.  A k-means clustering algorithm , 1979 .

[2]  N. L. Johnson,et al.  Multivariate Analysis , 1958, Nature.

[3]  Ravi S. Menon,et al.  Functional brain mapping by blood oxygenation level-dependent contrast magnetic resonance imaging. A comparison of signal characteristics with a biophysical model. , 1993, Biophysical journal.

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

[5]  Abdelmonem A. Afifi,et al.  Statistical Analysis: A Computer Oriented Approach. , 1973 .

[6]  Vincent Kanade,et al.  Clustering Algorithms , 2021, Wireless RF Energy Transfer in the Massive IoT Era.

[7]  J. Reichenbach,et al.  High-resolution, multiple gradient-echo functional MRI at 1.5 T. , 1999, Magnetic Resonance Imaging.

[8]  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.

[9]  R. M. Weisskoff,et al.  Temporal correlation in fMRI of the visual cortex: Impact on imaging rate , 1996, NeuroImage.

[10]  Robert Turner,et al.  Functional mapping of the human brain with magnetic resonance imaging , 1995 .

[11]  Maurice K. Wong,et al.  Algorithm AS136: A k-means clustering algorithm. , 1979 .

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

[13]  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.

[14]  Jean A. Tkach,et al.  2D and 3D high resolution gradient echo functional imaging of the brain: Venous contributions to signal in motor cortex studies , 1994, NMR in biomedicine.

[15]  J. R. Koehler,et al.  Modern Applied Statistics with S-Plus. , 1996 .

[16]  K. Kwong.  Functional magnetic resonance imaging with echo planar imaging. , 1995, Magnetic resonance quarterly.

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

[18]  Ewert Bengtsson,et al.  Using principal component analysis to visualize the spatial distribution of functional areas of the brain as studied with MRI during motor and sensory activation , 1994, Medical Imaging.

[19]  J. E. Jackson.  A User's Guide to Principal Components , 1991 .

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

[21]  J. Edward Jackson,et al.  A User's Guide to Principal Components. , 1991 .

[22]  Karl J. Friston,et al.  Analysis of functional MRI time‐series , 1994, Human Brain Mapping.

[23]  Ewald Moser,et al.  Explorative signal processing in functional MR imaging , 1999, Int. J. Imaging Syst. Technol..

[24]  A. Kleinschmidt,et al.  Brain or veinoxygenation or flow? On signal physiology in functional MRI of human brain activation , 1994, NMR in biomedicine.

[25]  J. Hajnal,et al.  Artifacts due to stimulus correlated motion in functional imaging of the brain , 1994, Magnetic resonance in medicine.

[26]  E. DeYoe,et al.  Reduction of physiological fluctuations in fMRI using digital filters , 1996, Magnetic resonance in medicine.

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