6 papers
QG-MIL: A Gated Transformer Aggregator for Domain-Agnostic Multiple Instance Learning in Medical Imaging
Luca Zedda, Davide Antonio Mura, Cecilia Di Ruberto +4
Attention-based Multiple Instance Learning aggregators in medical imaging are prone to attention concentration, producing overconfident and unstable predictions. We introduce QG-MI…
OmniRad: A Radiological Foundation Model for Multi-Task Medical Image Analysis
Luca Zedda, Andrea Loddo, Cecilia Di Ruberto
Radiological analysis increasingly benefits from pretrained visual representations that can support heterogeneous downstream tasks across imaging modalities. In this work, we intro…
RedDino: A foundation model for red blood cell analysis
Luca Zedda, Andrea Loddo, Cecilia Di Ruberto +1
Red blood cells (RBCs) are essential to human health, and their precise morphological analysis is important for diagnosing hematological disorders. Despite the promise of foundatio…
From User Preferences to Optimization Constraints Using Large Language Models
Manuela Sanguinetti, Alessandra Perniciano, Luca Zedda +3
This work explores using Large Language Models (LLMs) to translate user preferences into energy optimization constraints for home appliances. We describe a task where natural langu…
Exploring Few-Shot Object Detection on Blood Smear Images: A Case Study of Leukocytes and Schistocytes
Davide Antonio Mura, Michela Pinna, Lorenzo Putzu +4
The detection of blood disorders often hinges upon the quantification of specific blood cell types. Variations in cell counts may indicate the presence of pathological conditions.…
A Comparative Analysis of Image Descriptors for Histopathological Classification of Gastric Cancer
Marco Usai, Andrea Loddo, Alessandra Perniciano +2
Gastric cancer ranks as the fifth most common and fourth most lethal cancer globally, with a dismal 5-year survival rate of approximately 20%. Despite extensive research on its pat…