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cs.CV2025
Prompt-Conditioned FiLM and Multi-Scale Fusion on MedSigLIP for Low-Dose CT Quality Assessment
Tolga Demiroglu, Mehmet Ozan Unal, Metin Ertas +1
We propose a prompt-conditioned framework built on MedSigLIP that injects textual priors via Feature-wise Linear Modulation (FiLM) and multi-scale pooling. Text prompts condition p…
cs.CV2025
LMM-IQA: Image Quality Assessment for Low-Dose CT Imaging
Kagan Celik, Mehmet Ozan Unal, Metin Ertas +1
Low-dose computed tomography (CT) represents a significant improvement in patient safety through lower radiation doses, but increased noise, blur, and contrast loss can diminish di…
cs.CV2025
Learnable Total Variation with Lambda Mapping for Low-Dose CT Denoising
Yusuf Talha Basak, Mehmet Ozan Unal, Metin Ertas +1
While Total Variation (TV) excels in noise reduction and edge preservation, its reliance on a scalar regularization parameter limits adaptivity. In this study, we present a Learnab…