20 citations · 26 across the 14 of their papers we have counts for
19 papers · 1 filter
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…
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…
Physics Informed Capsule Enhanced Variational AutoEncoder for Underwater Image Enhancement
Niki Martinel, Rita Pucci
We present a novel dual-stream architecture that achieves state-of-the-art underwater image enhancement by explicitly integrating the Jaffe-McGlamery physical model with capsule cl…
Pyramid-based Mamba Multi-class Unsupervised Anomaly Detection
Nasar Iqbal, Niki Martinel
Recent advances in convolutional neural networks (CNNs) and transformer-based methods have improved anomaly detection and localization, but challenges persist in precisely localizi…
SkelMamba: A State Space Model for Efficient Skeleton Action Recognition of Neurological Disorders
Niki Martinel, Mariano Serrao, Christian Micheloni
We introduce a novel state-space model (SSM)-based framework for skeleton-based human action recognition, with an anatomically-guided architecture that improves state-of-the-art pe…
CE-VAE: Capsule Enhanced Variational AutoEncoder for Underwater Image Enhancement
Rita Pucci, Niki Martinel
Unmanned underwater image analysis for marine monitoring faces two key challenges: (i) degraded image quality due to light attenuation and (ii) hardware storage constraints limitin…