3 papers
cs.CV2026
H3D-MarNet: Wavelet-Guided Dual-Path Learning for Metal Artifact Suppression and CT Modality Transformation for Radiotherapy Workflows
Mubashara Rehman, Niki Martinel, Michele Avanzo +2
Metal artifacts in computed tomography (CT) severely degrade image quality, compromising diagnostic accuracy and radiotherapy planning, especially in cancer patients with high-dens…
cs.CV2025
ReMAR-DS: Recalibrated Feature Learning for Metal Artifact Reduction and CT Domain Transformation
Mubashara Rehman, Niki Martinel, Michele Avanzo +2
Artifacts in kilo-Voltage CT (kVCT) imaging degrade image quality, impacting clinical decisions. We propose a deep learning framework for metal artifact reduction (MAR) and domain…
eess.IV2024
MAR-DTN: Metal Artifact Reduction using Domain Transformation Network for Radiotherapy Planning
Belén Serrano-Antón, Mubashara Rehman, Niki Martinel +5
For the planning of radiotherapy treatments for head and neck cancers, Computed Tomography (CT) scans of the patients are typically employed. However, in patients with head and nec…