5 papers
CG-GLORE: A Conjugate Gradient-Based Global-Local Regularization Network for Sparse-View CT Reconstruction
Tran Xuan Hieu Le, Doanh C. Bui, Vu Trung Duong Le +5
Sparse-view computed tomography (CT) reduces radiation dose by acquiring fewer projection views, but the resulting inverse problem is highly ill-posed and often produces severe str…
BREIT: A Framework for Brain Stroke Reconstruction using Multi-Frequency 3D EIT
Djahid Abdelmoumene, Ishak Ayad, Maï K. Nguyen +1
Multi-Frequency Electrical Impedance Tomography (MF-EIT) is a non-invasive, low-cost modality that reconstructs electrical property distributions from boundary voltages. For stroke…
MergeSlide: Continual Model Merging and Task-to-Class Prompt-Aligned Inference for Lifelong Learning on Whole Slide Images
Doanh C. Bui, Ba Hung Ngo, Hoai Luan Pham +3
Lifelong learning on Whole Slide Images (WSIs) aims to train or fine-tune a unified model sequentially on cancer-related tasks, reducing the resources and effort required for data…
UnWave-Net: Unrolled Wavelet Network for Compton Tomography Image Reconstruction
Ishak Ayad, Cécilia Tarpau, Javier Cebeiro +1
Computed tomography (CT) is a widely used medical imaging technique to scan internal structures of a body, typically involving collimation and mechanical rotation. Compton scatter…
QN-Mixer: A Quasi-Newton MLP-Mixer Model for Sparse-View CT Reconstruction
Ishak Ayad, Nicolas Larue, Maï K. Nguyen
Inverse problems span across diverse fields. In medical contexts, computed tomography (CT) plays a crucial role in reconstructing a patient's internal structure, presenting challen…