Proposes a multimodal model with cross-attention and missingness-aware dictionary learning for robust DICOM series classification that outperforms image-only, metadata-only, and other multimodal baselines on liver MRI datasets.
Academic Radiology32(3), 1192–1203 (Mar 2025)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.IV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Revisiting Integration of Image and Metadata for DICOM Series Classification: Cross-Attention and Dictionary Learning
Proposes a multimodal model with cross-attention and missingness-aware dictionary learning for robust DICOM series classification that outperforms image-only, metadata-only, and other multimodal baselines on liver MRI datasets.