VCC-DSA uses a vascular consistency constraint and self-evolving training data to suppress motion artifacts in DSA, reporting 73.4% PSNR and 8.56% SSIM gains over other methods.
Title resolution pending
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
-
VCC-DSA: A Novel Vascular Consistency Constrained DSA Imaging Model for Motion Artifact Suppression
VCC-DSA uses a vascular consistency constraint and self-evolving training data to suppress motion artifacts in DSA, reporting 73.4% PSNR and 8.56% SSIM gains over other methods.