Move on to other datasets and aggregate datasets

[hermancollin]

The TEM dataset was the biggest of our private datasets, but we will also need to move on to other modalities to compare performance with ivadomed and nnunetv2.

The ultimate goal of using SAM was to train a single "foundation" model for every type of contrasts/resolution, so we will eventually want to train SAM on an aggregation of all our private datasets. For comparison, we will need to train models on every dataset individually before aggregating. This necessary step will also allow us to fix bugs with these datasets before we use them all at once.