Regularized iterative reconstruction in tensor tomography using gradient constraints

This paper investigates the iterative reconstruction of the tensor field in diffusion tensor magnetic resonance imaging. The gradient constraints on eigenvalue and tensor components images of diffusion tensor were explored. A computer generated phantom was used to simulate the diffusion tensor in a cardiac MRI study, where the diffusion model depended upon the fiber structure of the myocardium. Computer simulations verify that the regularized methods provide improved reconstruction of the tensor principal directions. The reconstruction from real data is also presented.