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| Main Authors: | , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.24676 |
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| _version_ | 1866918150544556032 |
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| author | Argiento, Benedetta Annovi, Alberto Capuani, Silvia Cacioppo, Matteo Ciardiello, Andrea Coccurello, Roberto Giagu, Stefano Giove, Federico Lonardo, Alessandro Cicero, Francesca Lo Maiuro, Alessandra Terracciano, Carlo Mancini Merola, Mario Montuori, Marco Nisticò, Emilia Perticaroli, Pierpaolo Rossi, Biagio Rossi, Cristian Rossi, Elvira Simula, Francesco Voena, Cecilia |
| author_facet | Argiento, Benedetta Annovi, Alberto Capuani, Silvia Cacioppo, Matteo Ciardiello, Andrea Coccurello, Roberto Giagu, Stefano Giove, Federico Lonardo, Alessandro Cicero, Francesca Lo Maiuro, Alessandra Terracciano, Carlo Mancini Merola, Mario Montuori, Marco Nisticò, Emilia Perticaroli, Pierpaolo Rossi, Biagio Rossi, Cristian Rossi, Elvira Simula, Francesco Voena, Cecilia |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_24676 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Real-Time Motion Correction in Magnetic Resonance Spectroscopy: AI solution inspired by fundamental science Argiento, Benedetta Annovi, Alberto Capuani, Silvia Cacioppo, Matteo Ciardiello, Andrea Coccurello, Roberto Giagu, Stefano Giove, Federico Lonardo, Alessandro Cicero, Francesca Lo Maiuro, Alessandra Terracciano, Carlo Mancini Merola, Mario Montuori, Marco Nisticò, Emilia Perticaroli, Pierpaolo Rossi, Biagio Rossi, Cristian Rossi, Elvira Simula, Francesco Voena, Cecilia Medical Physics 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. |
| title | Real-Time Motion Correction in Magnetic Resonance Spectroscopy: AI solution inspired by fundamental science |
| topic | Medical Physics |
| url | https://arxiv.org/abs/2509.24676 |