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cs.CV2026
Vascular anatomy-aware self-supervised pre-training for X-ray angiogram analysis
De-Xing Huang, Chaohui Yu, Xiao-Hu Zhou +8
X-ray angiography is the gold standard imaging modality for cardiovascular diseases. However, current deep learning approaches for X-ray angiogram analysis are severely constrained…
cs.CV2026
A Contrastive Pre-trained Foundation Model for Deciphering Imaging Noisomics across Modalities
Yuanjie Gu, Yiqun Wang, Chaohui Yu +4
Characterizing imaging noise is notoriously data-intensive and device-dependent, as modern sensors entangle physical signals with complex algorithmic artifacts. Current paradigms s…
cs.CV2024
Deep RAW Image Super-Resolution. A NTIRE 2024 Challenge Survey
Marcos V. Conde, Florin-Alexandru Vasluianu, Radu Timofte +32
This paper reviews the NTIRE 2024 RAW Image Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Super-Resolution could be essential in…