collaborators

6 papers

cs.CV2026

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…

cs.MA2026

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…

cs.CV2026

Cross Modality Image Translation In Medical Imaging Using Generative Frameworks

Giulia Romoli, Alessia Capoccia, Filippo Ruffini +20

Medical image-to-image (I2I) translation enables virtual scanning, i.e. the synthesis of a target imaging modality from a source one without additional acquisitions. Despite growin…

physics.med-ph2026

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…

cs.AI2026

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…

cs.AI2025

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…