7 papers
Morphology-Aware KOA Classification: Integrating Graph Priors with Vision Models
Marouane Tliba, Mohamed Amine Kerkouri, Yassine Nasser +4
Knee osteoarthritis (KOA) diagnosis from radiographs remains challenging due to the subtle morphological details that standard deep learning models struggle to capture effectively.…
Diffusion-based Counterfactual Augmentation: Towards Robust and Interpretable Knee Osteoarthritis Grading
Zhe Wang, Yuhua Ru, Aladine Chetouani +9
Automated grading of Knee Osteoarthritis (KOA) from radiographs is challenged by significant inter-observer variability and the limited robustness of deep learning models, particul…
MoEDiff-SR: Mixture of Experts-Guided Diffusion Model for Region-Adaptive MRI Super-Resolution
Zhe Wang, Yuhua Ru, Aladine Chetouani +7
Magnetic Resonance Imaging (MRI) at lower field strengths (e.g., 3T) suffers from limited spatial resolution, making it challenging to capture fine anatomical details essential for…
Feasibility study for reconstruction of knee MRI from one corresponding X-ray via CNN
Zhe Wang, Aladine Chetouani, Rachid Jennane
Generally, X-ray, as an inexpensive and popular medical imaging technique, is widely chosen by medical practitioners. With the development of medical technology, Magnetic Resonance…
Distillation-Driven Diffusion Model for Multi-Scale MRI Super-Resolution: Make 1.5T MRI Great Again
Zhe Wang, Yuhua Ru, Fabian Bauer +7
Magnetic Resonance Imaging (MRI) offers critical insights into microstructural details, however, the spatial resolution of standard 1.5T imaging systems is often limited. In contra…
Key-Exchange Convolutional Auto-Encoder for Data Augmentation in Early Knee Osteoarthritis Detection
Zhe Wang, Aladine Chetouani, Mohamed Jarraya +7
Knee Osteoarthritis (KOA) is a common musculoskeletal condition that significantly affects mobility and quality of life, particularly in elderly populations. However, training deep…