Analytical computation of the eigenvalues and eigenvectors in DT-MRI.
In this paper a noniterative algorithm to be used for the analytical determination of the sorted eigenvalues and corresponding orthonormalized eigenvectors obtained by diffusion tensor magnetic resonance imaging (DT-MRI) is described. The algorithm uses the three invariants of the raw water spin self-diffusion tensor represented by a 3 x 3 positive definite matrix and certain math functions that do not require iteration. The implementation requires a positive definite mask to preserve the physical meaning of the eigenvalues. This algorithm can increase the speed of eigenvalue/eigenvector calculations by a factor of 5-40 over standard iterative Jacobi or singular-value decomposition techniques. This approach may accelerate the computation of eigenvalues, eigenvalue-dependent metrics, and eigenvectors especially when having high-resolution measurements with large numbers of slices and large fields of view.
Hasan
K M
KM
Department of Medical Physics, University of Wisconsin, Madison, Wisconsin 53705-2280, USA. kmhasan@facstaff.wisc.edu
Basser
P J
PJ
Parker
D L
DL
Alexander
A L
AL
D000465:Algorithms; D008279:Magnetic Resonance Imaging; D019047:Phantoms, Imaging; D055585:Physical Phenomena; D010825:Physics