Incorporating independent component analysis to Q-ball imaging for diffusion orientation distribution reconstruction

In this paper, we investigate the incorporation of independent component analysis (ICA) with Q-ball imaging (QBI) to extract information on the diffusion orientation distribution function (ODF) from an inner voxel. In our approach, the ICA algorithm is applied to a mixture of ODFs which are constructed based on the analytical QBI solution. The numerical simulation results demonstrate that the proposed ICA framework can not only successfully separate the diffusion ODF from the noisy diffusion data, but also achieves better performance compared with a QBI solution when the data has a low signal to noise ratio (SNR).

[1]  Alan Connelly,et al.  Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution , 2004, NeuroImage.

[2]  Vince D. Calhoun,et al.  Comparison of blind source separation algorithms for FMRI using a new Matlab toolbox: GIFT , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[3]  R. Deriche,et al.  Regularized, fast, and robust analytical Q‐ball imaging , 2007, Magnetic resonance in medicine.

[4]  Duan Xu,et al.  Q‐ball reconstruction of multimodal fiber orientations using the spherical harmonic basis , 2006, Magnetic resonance in medicine.

[5]  P. Basser,et al.  MR diffusion tensor spectroscopy and imaging. , 1994, Biophysical journal.

[6]  N. Makris,et al.  High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity , 2002, Magnetic resonance in medicine.

[7]  D. Tuch.  Q‐ball imaging , 2004, Magnetic resonance in medicine.

[8]  V. Haughton,et al.  Independent component analysis applied to diffusion tensor MRI , 2002, Magnetic resonance in medicine.

[9]  Rex E. Jung,et al.  Multimodal and Multi-Tissue Measures of Connectivity Revealed by Joint Independent Component Analysis , 2008, IEEE Journal of Selected Topics in Signal Processing.

[10]  Terrence J. Sejnowski,et al.  An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.

[11]  V. Wedeen,et al.  Mapping fiber orientation spectra in cerebral white matter with Fourier-transform diffusion MRI , 2000 .

[12]  M. Singh,et al.  Estimation of multiple fiber orientations from diffusion tensor MRI using independent component analysis , 2005, IEEE Transactions on Nuclear Science.

[13]  Lawrence R. Frank,et al.  Decreased white matter integrity in late-myelinating fiber pathways in Alzheimer's disease supports retrogenesis , 2009, NeuroImage.

[14]  R. Deriche,et al.  Apparent diffusion coefficients from high angular resolution diffusion imaging: Estimation and applications , 2006, Magnetic resonance in medicine.

[15]  Kalvis M. Jansons,et al.  Persistent angular structure: new insights from diffusion magnetic resonance imaging data , 2003 .

[16]  Baba C. Vemuri,et al.  Resolution of complex tissue microarchitecture using the diffusion orientation transform (DOT) , 2006, NeuroImage.