An unsupervised pipeline that uses CLIP to label slices, CAM to localize tumors, SAM to generate pseudo-masks, and self-training with similarity filtering reaches 85.6% Dice on BraTS2020 whole-tumor segmentation.
Ethical ap- proval was not required as confirmed by the license attached with the open-access data
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation
An unsupervised pipeline that uses CLIP to label slices, CAM to localize tumors, SAM to generate pseudo-masks, and self-training with similarity filtering reaches 85.6% Dice on BraTS2020 whole-tumor segmentation.