Linear invariant tensor interpolation applied to cardiac diffusion tensor MRI

摘要: Purpose: Various methods exist for interpolating diffusion tensor fields, but none of them linearly interpolate shape attributes. Linear interpolation is expected not to introduce spurious changes in shape. Methods: Herein we define a new linear invariant (LI) method that interpolates components (tensor invariants) and recapitulates the interpolated from invariants eigenvectors tensor. The LI compared Euclidean (EU), affine-invariant Riemannian (AI), log-Euclidean (LE) geodesic-loxodrome (GL) using both synthetic field three experimentally measured cardiac DT-MRI datasets. Results: EU, AI, LE significant microstructural bias, which can be avoided through use GL or LI. Conclusion: introduces least performs very similarly at substantially reduced computational cost.