Unsupervised identification of white matter tracts in a mouse brain using a directional correlation-based region growing (DCRG) algorithm.

The inner product of the major eigenvectors of adjacent pixels, known as the directional correlation (DC), has been used previously as a quantitative index to investigate directional similarity in white matter (WM) tracts. A high degree of directional similarity (i.e.

Noquist: reduced field-of-view imaging by direct Fourier inversion.

A novel technique called "Noquist" is introduced for the acceleration of dynamic cardiac magnetic resonance imaging (CMRI). With the use of this technique, a more sparsely sampled dynamic image sequence is reconstructed correctly, without Nyquist foldover artifact. Unlike most other reduced field-of-view (rFOV) methods, Noquist does not rely on data substitution or temporal interpolation to reconstruct the dynamic image sequence.

Directional correlation characterization and classification of white matter tracts.

To study the architectural characteristics of white matter (WM) tracts, the directional correlation (DC), defined as the inner product of the major eigenvector of adjacent pixels, was used as a quantitative index to investigate directional similarity in WM tracts. A region-growing algorithm was employed to propagate an area from a seed point as a function of the DC threshold (DCt) to critically evaluate the directional properties of WM tracts. As the DCt was increased, more pixels were excluded from the propagated region as their DC fell below the DCt, and neighboring WM tracts could be distinguished as the area decreased.