Recent advances and future trends in Artificial Intelligence (A1)-based methods for biomedical imaging are discussed in this work. Among them, a focus is given on the “three-steps” Learning-by-Examples (3-LBE) paradigm which allows the efficient/effective generation of robust and accurate surrogate models (SMs) for the realtime inversion of electromagnetic (EM) data. Moreover, the pillar ideas and concepts of the System-by-Design (SbD) framework are outlined when addressing the solution of complex inverse scattering problems (ISPs) arising in several biomedical microwave imaging scenarios.
AI-Based Methodologies for Next-Generation Biomedical Imaging: Recent Advances and Future Trends / Salucci, Marco; Lusa, Samantha; Poli, Lorenzo; Polo, Alessandro; Tosi, Luca; Massa, Andrea. - STAMPA. - (2024), pp. 1-3. ( 9th International Conference on Smart and Sustainable Technologies (SpliTech) University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture (FESB) and Hotel Elaphusa, hrv 25th June - 28th June 2024) [10.23919/splitech61897.2024.10612417].
AI-Based Methodologies for Next-Generation Biomedical Imaging: Recent Advances and Future Trends
Salucci, Marco;Lusa, Samantha;Poli, Lorenzo;Polo, Alessandro;Tosi, Luca;Massa, Andrea
2024-01-01
Abstract
Recent advances and future trends in Artificial Intelligence (A1)-based methods for biomedical imaging are discussed in this work. Among them, a focus is given on the “three-steps” Learning-by-Examples (3-LBE) paradigm which allows the efficient/effective generation of robust and accurate surrogate models (SMs) for the realtime inversion of electromagnetic (EM) data. Moreover, the pillar ideas and concepts of the System-by-Design (SbD) framework are outlined when addressing the solution of complex inverse scattering problems (ISPs) arising in several biomedical microwave imaging scenarios.| File | Dimensione | Formato | |
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