98 citations · 131 across the 6 of their papers we have counts for
6 papers
One-Shot Data Selection for Medical Image Classification via Graph Coverage
Zahiriddin Rustamov, Nadia Badawi, Rafat Damseh +1
Training medical image classifiers on entire datasets is wasteful when annotation budgets are limited: not all samples contribute equally, yet acquiring expert labels is expensive.…
Large AI Models in Dental Healthcare: From General-Purpose Systems to Domain-Specific Foundation Models
Sema Helali, Lina Abu Nada, Sausan Al Kawas +3
Background: Oral diseases affect nearly 3.5 billion people worldwide, yet the comparative clinical potential of large-scale AI models in dentistry remains poorly understood. Three…
GAIS: A Novel Approach to Instance Selection with Graph Attention Networks
Zahiriddin Rustamov, Ayham Zaitouny, Rafat Damseh +1
Instance selection (IS) is a crucial technique in machine learning that aims to reduce dataset size while maintaining model performance. This paper introduces a novel method called…
Transformer-based Image and Video Inpainting: Current Challenges and Future Directions
Omar Elharrouss, Rafat Damseh, Abdelkader Nasreddine Belkacem +2
Image inpainting is currently a hot topic within the field of computer vision. It offers a viable solution for various applications, including photographic restoration, video editi…
A Deep Learning Framework for Spatiotemporal Ultrasound Localization Microscopy
Léo Milecki, Jonathan Porée, Hatim Belgharbi +6
Ultrasound Localization Microscopy can resolve the microvascular bed down to a few micrometers. To achieve such performance microbubble contrast agents must perfuse the entire micr…
Laplacian Flow Dynamics on Geometric Graphs for Anatomical Modeling of Cerebrovascular Networks
Rafat Damseh, Patrick Delafontaine-Martel, Philippe Pouliot +2
Generating computational anatomical models of cerebrovascular networks is vital for improving clinical practice and understanding brain oxygen transport. This is achieved by extrac…