Real-Time Motion Correction in Magnetic Resonance Spectroscopy: AI solution inspired by fundamental science
Benedetta Argiento, Alberto Annovi, Silvia Capuani, Matteo Cacioppo, Andrea Ciardiello, Roberto Coccurello, Stefano Giagu, Federico Giove, Alessandro Lonardo, Francesca Lo Cicero, Alessandra Maiuro, Carlo Mancini Terracciano, Mario Merola, Marco Montuori, Emilia Nisticò, Pierpaolo Perticaroli, Biagio Rossi, Cristian Rossi, Elvira Rossi, Francesco Simula, Cecilia Voena
公開日: 2025/9/29
Abstract
Magnetic Resonance Spectroscopy (MRS) is a powerful non-invasive tool for metabolic tissue analysis but is often degraded by patient motion, limiting clinical utility. The RECENTRE project (REal-time motion CorrEctioN in magneTic Resonance) presents an AI-driven, real-time motion correction pipeline based on optimized GRU networks, inspired by tagging and fast-trigger algorithms from high-energy physics. Models evaluated on held-out test sets achieve good predictive performance and overall positive framewise displacement (FD) gains. These results demonstrate feasibility for prospective scanner integration; future work will complete in-vivo validation.