Which anatomical model to use as "ground truth" for validating an MRI segmentation method? I am research in brain segmentation task that classify a brain in to 3 classes : White Matter, Gray Matter and CSF. To validate my method, I used Dice Coefficient that compare my result and ground truth result. However, I am confusing about ground truth result. As I found that ground truth brain of brainweb service has two models: fuzzy and discrete models. 

A fuzzy phantom will specify a mixture of tissue classes for each voxel (eg. a voxel might contain 90% grey matter and 10% white matter). A fuzzy phantom was used to describe the tissue within each voxel during the simulation process.

A discrete phantom specifies the tissue type with the largest proportion in each voxel. A discrete phantom was not used in the simulation process. However a user might use this phantom when comparing simulated data against the underlying tissue types (eg. a user might have a classification algorithm which classifies each voxel into one specific tissue type).

They suggest that "If your method attempts to estimate the partial volume (that is, the tissue fractions in each voxel) then the fuzzy model is probably what you want. Otherwise, the discrete model will probably do..."

From that information, Which model can I used for segmentation task?

As my knowledge, I think that discrete model must be used. How about you?
Your question practically answers itself in the "If your method attempts to estimate the partial volume then the fuzzy model is probably what you want. Otherwise, the discrete model will probably do..." quote.

So: if you're only going to segment each voxel into one of white/gray/CSF then yes, the discrete one seems the appropriate one to use.