Hi MONAI team,
I’m trying to understand the origin of the pretrained weight:
ssl_pretrained_weights.pth (from MONAI-extra-test-data, ~719MB).
From the checkpoint structure, it contains:
- encoder.*
- decoder*
- out.conv.*
- encoder.mask_token
which looks like a full encoder-decoder model.
I found the following description in the tutorial README:
https://github.com/Project-MONAI/tutorials/blob/main/self_supervised_pretraining/swinunetr_pretrained/README.md
"The entire SwinUNETR model including encoder and decoder was trained end-to-end using self-supervised learning techniques as outlined in [1]."
However, it is unclear what [1] refers to in terms of actual training code or pipeline.
Could you please help clarify:
-
What exactly does reference [1] correspond to?
(Is it a specific paper, or an internal training implementation?)
-
Was ssl_pretrained_weights.pth trained using the
research-contributions/SwinUNETR/Pretrain (SSLHead: rotation + contrastive + reconstruction),
or a different encoder-decoder / autoencoder-style pretraining pipeline?
A short clarification would already help a lot.
Thanks!