most citedA General Method to Incorporate Spatial Information into Loss Functions for GAN-based Super-resolution Models

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Physics-Informed Image Restoration via Progressive PDE Integration

Shamika Likhite, Santiago López-Tapia, Aggelos K. Katsaggelos

Motion blur, caused by relative movement between camera and scene during exposure, significantly degrades image quality and impairs downstream computer vision tasks such as object…

eess.IV2025

Diffusion-Based Limited-Angle CT Reconstruction under Noisy Conditions

Jiaqi Guo, Santiago López-Tapia

Limited-Angle Computed Tomography (LACT) is a challenging inverse problem where missing angular projections lead to incomplete sinograms and severe artifacts in the reconstructed i…

eess.IV2025★ 1 cited

ScarNet: A Novel Foundation Model for Automated Myocardial Scar Quantification from LGE in Cardiac MRI

Neda Tavakoli, Amir Ali Rahsepar, Brandon C. Benefield +9

Background: Late Gadolinium Enhancement (LGE) imaging is the gold standard for assessing myocardial fibrosis and scarring, with left ventricular (LV) LGE extent predicting major ad…

eess.IV2024

DRL-STNet: Unsupervised Domain Adaptation for Cross-modality Medical Image Segmentation via Disentangled Representation Learning

Hui Lin, Florian Schiffers, Santiago López-Tapia +3

Unsupervised domain adaptation (UDA) is essential for medical image segmentation, especially in cross-modality data scenarios. UDA aims to transfer knowledge from a labeled source…

eess.IV2024★ 1 cited

A General Method to Incorporate Spatial Information into Loss Functions for GAN-based Super-resolution Models

Xijun Wang, Santiago López-Tapia, Alice Lucas +3

Generative Adversarial Networks (GANs) have shown great performance on super-resolution problems since they can generate more visually realistic images and video frames. However, t…