| dc.contributor.advisor | Cooley, Clarissa Z. | |
| dc.contributor.advisor | White, Jacob | |
| dc.contributor.author | Flynn, John M. | |
| dc.date.accessioned | 2025-09-18T14:28:00Z | |
| dc.date.available | 2025-09-18T14:28:00Z | |
| dc.date.issued | 2025-05 | |
| dc.date.submitted | 2025-06-23T14:01:55.600Z | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/162700 | |
| dc.description.abstract | Portable, Low-Field MRI broadens access and enables numerous new applications such as point-of-care. Operating outside an RF-shielded room introduces electromagnetic interference (EMI), degrading further the signal-to-noise ratio (SNR) which is already diminished due to the lower magnetic fields used in portable imaging. Existing methods to reduce EMI perform well in simple noise environments, but can struggle with more complex profiles. Relaxing the linear assumptions is hypothesized to bring more robust mitigation algorithms. A system-wide characterization of SNR challenges was carried out on a rebuilt 800G scanner, existing techniques were validated, and new signal processing approaches were explored to drive image quality upwards. Various analytical approaches showed promise, such as dynamic coils/preamps, averaging methods, calibration, and smoothing methods. Groundwork was laid for learning-based methods throughout the pipeline. This work serves as an important baseline for the numerous experiments necessary for the full-system optimization. | |
| dc.publisher | Massachusetts Institute of Technology | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) | |
| dc.rights | Copyright retained by author(s) | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.title | Mitigating Electromagnetic Interference in Unshielded MRI: Implementation, Experimentation, and Future Directions | |
| dc.type | Thesis | |
| dc.description.degree | M.Eng. | |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | |
| mit.thesis.degree | Master | |
| thesis.degree.name | Master of Engineering in Electrical Engineering and Computer Science | |