DTI-density

While visualizing the diffusion tensor MRI (DTI) dataset using streamtubes, the unit (1x1x1) resolution in full volume seeding approach has been used as default parameters and the resulting tractography contains very dense geometries that causes visual complexity impeding the exploration of DTI visualizations. However, questions like "if the unit seeding resolution is optimal for visualizing either whole brain model or tract-of-interest (TOI)", "if not, what the optimal choice of seeding should be", and especially, "how quantitatively the choice of the fiber tracking parameter, seeding resolution, connects with the informativeness and meaningfulness of DTI visualizations".

In this project therefore, we investigate five scales of seeding resolution with the same brain dataset and measure the effect of the resolution difference on user performance on a set of tasks typical of those conducted by neurological experts.