A Review on Interpolation Methods for Diffusion Tensor Images

Abstract

Diffusion tensor imaging measures three-dimensional distribution of water molecule displacement in tissues, and has been widely used to study the structure of the brain. The technique has attracted wide research interests in recent years. Interpolation is often needed in the acquisition and reconstruction of diffusion tensor images to improve spatial resolution and/or facilitate visualization, especially when the images are used for white matter fiber tracking and registration in human brain. In this paper, the existing tensor interpolation methods are reviewed. The theory underlying the interpolation methods is described first. The technical challenges and limitations of the currently-used methods are then reviewed, followed by the introduction to the evaluation indices of the interpolation methods. The performance of typical interpolation methods is then compared with simulated data and real experimental data. The future direction of the development of tensor interpolation method is suggested.

Keywords

• diffusion tensor imaging (DTI)
• tensor interpolation
• Euler angle
• quaternion
• fractional anisotropy