27 February 2009 Approximating high angular resolution apparent diffusion coefficient profiles using spherical harmonics under biGaussian assumption
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Abstract
Magnetic Resonance Imaging (MRI) techniques have achieved much importance in providing visual and quantitative information of human body. Diffusion MRI is the only non-invasive tool to obtain information of the neural fiber networks of the human brain. The traditional Diffusion Tensor Imaging (DTI) is only capable of characterizing Gaussian diffusion. High Angular Resolution Diffusion Imaging (HARDI) extends its ability to model more complex diffusion processes. Spherical harmonic series truncated to a certain degree is used in recent studies to describe the measured non-Gaussian Apparent Diffusion Coefficient (ADC) profile. In this study, we use the sampling theorem on band-limited spherical harmonics to choose a suitable degree to truncate the spherical harmonic series in the sense of Signal-to-Noise Ratio (SNR), and use Monte Carlo integration to compute the spherical harmonic transform of human brain data obtained from icosahedral schema.
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Ning Cao, Xuwei Liang, Qi Zhuang, Jun Zhang, "Approximating high angular resolution apparent diffusion coefficient profiles using spherical harmonics under biGaussian assumption", Proc. SPIE 7262, Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging, 726204 (27 February 2009); doi: 10.1117/12.812944; https://doi.org/10.1117/12.812944
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