5 papers · 1 filter
CT-DegradBench: A Physics-Informed Benchmark for CT Degradation Detection and Severity Estimation
Yousra Nabila Taifour, Marouane Tliba, Zuheng Ming +9
Computed tomography (CT) images are frequently degraded by acquisition artifacts, including noise, blur, streaking, aliasing, and metal artifacts. Yet CT enhancement is still large…
D-PerceptCT: Deep Perceptual Enhancement for Low-Dose CT Images
Taifour Yousra Nabila, Azeddine Beghdadi, Marie Luong +3
Low Dose Computed Tomography (LDCT) is widely used as an imaging solution to aid diagnosis and other clinical tasks. However, this comes at the price of a deterioration in image qu…
Toward Better Optimization of Low-Dose CT Enhancement: A Critical Analysis of Loss Functions and Image Quality Assessment Metrics
Taifour Yousra, Beghdadi Azeddine, Marie Luong +1
Low-dose CT (LDCT) imaging is widely used to reduce radiation exposure to mitigate high exposure side effects, but often suffers from noise and artifacts that affect diagnostic acc…
A New Lightweight Hybrid Graph Convolutional Neural Network -- CNN Scheme for Scene Classification using Object Detection Inference
Ayman Beghdadi, Azeddine Beghdadi, Mohib Ullah +2
Scene understanding plays an important role in several high-level computer vision applications, such as autonomous vehicles, intelligent video surveillance, or robotics. However, t…
CD-COCO: A Versatile Complex Distorted COCO Database for Scene-Context-Aware Computer Vision
Ayman Beghdadi, Azeddine Beghdadi, Malik Mallem +2
The recent development of deep learning methods applied to vision has enabled their increasing integration into real-world applications to perform complex Computer Vision (CV) task…