This is a terrific tool, congrats to the NVIDIA team behind this!
Presumably AI assisted annotation allows creation of new ground truth (eg for transfer learning) where the existing pre-trained segmentation model only approximates the desired segmentation, which can then be used to train a more accurate model.
After training a new segmentation model with new ground truth made with AI assisted annotations, how might one convert this new segmentation model into a new annotation model for another round of transfer/active learning?
In brief, how is the model annotation_ct_liver different from segmentation_ct_liver? How could I take a custom segmentation model segmentation_ct_custom_liver and create a custom annotation model annotation_ct_custom_liver?
Thanks for your help!