6 papers
Structured Spectral Graph Representation Learning for Multi-label Abnormality Analysis from 3D CT Scans
Theo Di Piazza, Carole Lazarus, Olivier Nempont +1
With the growing volume of CT examinations, there is an increasing demand for automated tools such as organ segmentation, abnormality detection, and report generation to support ra…
ChronoSurv: A Clinical Pathway-Guided Graph Framework for Multimodal Survival Analysis
Hugo Miccinilli, Theo Di Piazza
Accurate survival prediction is essential for personalized treatment planning in head and neck cancer, yet remains challenging due to the heterogeneous and high-dimensional nature…
CT-AGRG: Automated Abnormality-Guided Report Generation from 3D Chest CT Volumes
Theo Di Piazza, Carole Lazarus, Olivier Nempont +1
The rapid increase of computed tomography (CT) scans and their time-consuming manual analysis have created an urgent need for robust automated analysis techniques in clinical setti…
Imitating Radiological Scrolling: A Global-Local Attention Model for 3D Chest CT Volumes Multi-Label Anomaly Classification
Theo Di Piazza, Carole Lazarus, Olivier Nempont +1
The rapid increase in the number of Computed Tomography (CT) scan examinations has created an urgent need for automated tools, such as organ segmentation, anomaly classification, a…
Structured Spectral Graph Learning for Anomaly Classification in 3D Chest CT Scans
Theo Di Piazza, Carole Lazarus, Olivier Nempont +1
With the increasing number of CT scan examinations, there is a need for automated methods such as organ segmentation, anomaly detection and report generation to assist radiologists…
An Ensemble-Based Two-Step Framework for Classification of Pap Smear Cell Images
Theo Di Piazza, Loic Boussel
Early detection of cervical cancer is crucial for improving patient outcomes and reducing mortality by identifying precancerous lesions as soon as possible. As a result, the use of…