3 citations · 4 across the 6 of their papers we have counts for
7 papers
Automated screening of privacy risks in medical AI
Konstantinos Vrettos, Eleftherios Tzanis, Haridimos Kondylakis +3
Medical artificial intelligence (AI) models are often shared without their training data, assuming this protects the patients who contributed them. However, a model can reveal whet…
Cross Modality Image Translation In Medical Imaging Using Generative Frameworks
Giulia Romoli, Alessia Capoccia, Filippo Ruffini +20
Magnetic Resonance Imaging (MRI), Computed Tomography (CT), and Positron Emission Tomography (PET) provide complementary information about tissues. Medical image-to-image (I2I) tra…
DosimeTron: Automating Personalized Monte Carlo Radiation Dosimetry in PET/CT with Agentic AI
Eleftherios Tzanis, Michail E. Klontzas, Antonios Tzortzakakis
Purpose: To develop and evaluate DosimeTron, an agentic AI system for automated patient-specific MC internal radiation dosimetry in PET/CT examinations. Materials and Methods: In t…
OpenRad: a Curated Repository of Open-access AI models for Radiology
Konstantinos Vrettos, Galini Papadaki, Emmanouil Brilakis +7
The rapid developments in artificial intelligence (AI) research in radiology have produced numerous models that are scattered across various platforms and sources, limiting discove…
The MAMA-MIA Challenge: Advancing Generalizability and Fairness in Breast MRI Tumor Segmentation and Treatment Response Prediction
Lidia Garrucho, Smriti Joshi, Kaisar Kushibar +43
Breast cancer is the most frequently diagnosed malignancy among women worldwide and a leading cause of cancer-related mortality. Dynamic contrast-enhanced magnetic resonance imagin…
ReclAIm: A Multi-Agent Framework for Monitoring and Correcting Performance Decline in Medical Imaging AI
Eleftherios Tzanis, Michail E. Klontzas
Purpose: To develop and evaluate a multi-agent framework (ReclAIm) for automated monitoring, detection, and correction of performance decline in medical image classification models…
Accurate and Energy Efficient: Local Retrieval-Augmented Generation Models Outperform Commercial Large Language Models in Medical Tasks
Konstantinos Vrettos, Michail E. Klontzas
Background The increasing adoption of Artificial Intelligence (AI) in healthcare has sparked growing concerns about its environmental and ethical implications. Commercial Large Lan…