The normal phase diffusion problem in magnetic resonance imaging ͑MRI͒ is treated by means of the Langevin equation for the phase variable using only the properties of the characteristic function of Gaussian random variables. The calculation may be simply extended to anomalous diffusion using a fractional generalization of the Langevin equation proposed by Lutz ͓E. Lutz, Phys. Rev. E 64, 051106 ͑2001͔͒ pertaining to the fractional Brownian motion of a free particle coupled to a fractal heat bath. The results compare favorably with diffusion-weighted experiments acquired in human neuronal tissue using a 3 T MRI scanner.

Discerning an underlying structure in the array of magnetic resonance (MR) imaging sequences and acronyms available is a bewildering task. Attempts have been made to present standard taxonomies of MR imaging sequences, primarily on the basis of their underlying physics. Despite this, it is difficult to usefully incorporate given taxonomies into routine clinical knowledge. The links, differences, and similarities among sequences are multidimensional and too complex for tabular presentation on the printed page. The authors present an interactive taxonomy of MR imaging sequences. With this graphical interface, the user can explore the changing relationships among a wide range of sequence types as they are viewed from different perspectives and through different associations, working through a natural learning process.

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