Noise-induced self-supervised hybrid UNet transformer for ischemic stroke segmentation with limited data annotations
Abstract We extend the Hybrid Unet Transformer (HUT) foundation model, which combines the advantages of the CNN and Transformer architectures with a noisy self-supervised approach, and demonstrate it in an ischemic stroke lesion segmentation task. We introduce a self-supervised approach using a nois...
Αποθηκεύτηκε σε:
| Κύριοι συγγραφείς: | , |
|---|---|
| Μορφή: | Artigo |
| Γλώσσα: | Inglês |
| Έκδοση: |
Nature Portfolio
2025-06-01
|
| Σειρά: | Scientific Reports |
| Θέματα: | |
| Διαθέσιμο Online: | https://doi.org/10.1038/s41598-025-04819-2 |
| Ετικέτες: |
Δεν υπάρχουν, Καταχωρήστε ετικέτα πρώτοι!
|