DC-Seg trains a single model that aligns anatomical features across MRI modalities with contrastive learning and adds a per-modality segmentation regularizer, yielding higher Dice scores when modalities are missing.
IEEE transactions on medical imag- ing 41(3), 621–632 (2021)
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
-
DC-Seg: Disentangled Contrastive Learning for Brain Tumor Segmentation with Missing Modalities
DC-Seg trains a single model that aligns anatomical features across MRI modalities with contrastive learning and adds a per-modality segmentation regularizer, yielding higher Dice scores when modalities are missing.