An Adaptive Interpolation of DT-MRI Based on Local Gradient Features

摘要

In vivo diffusion tensor data obtained with diffusion tensor magnetic resonance imaging (DT-MRI) can be used to estimate fibre tract trajectories in white matter in the brain. However, interpolation is usually necessary in the application of diffusion tensor since the acquired images have low resolution. In this paper, we present an efficient adaptive interpolation method for diffusion tensor images based on the use of local gradient features. The application of local gradients to the structure of conventional linear interpolation produces better results, preserving boundaries of tensor images and the constraint of positive definiteness of tensor fields. Besides, the proposed method can be easily implemented and does efficiently and quickly, which is important in processing vast data. Experimental results on synthetic and real DT-MRI data sets finally illustrates the proposed interpolation method, which demonstrated that the proposed method outperforms the conventional linear interpolation scheme.