The professionally focused MEng in Biomedical Imaging equips engineers with the physics, AI, and regulatory know-how to push boundaries from sub-cellular microscopy to whole-body MR. Courses dive into pulse-sequence design, radiomics, and FDA 510(k) pathways, while practicum teams optimize PET reconstruction on GPU clusters or build AR overlays for surgical navigation. One calendar year later, graduates power innovation at Philips, Siemens Healthineers, or imaging-AI start-ups.
Deep-learning super-resolution pipeline for low-dose CT
Zero-TE MRI sequence minimizing acoustic noise for pediatric scans
3-D ultrasonic holography system for real-time tumor ablation monitoring
Radiomic signature predicting immunotherapy response in lung cancer
Augmented-reality neuronavigation overlay for skull-base surgery
Photon-counting detector characterization for spectral CT
Federated-learning framework training MRI models across hospitals
K-space sampling optimization via reinforcement learning
Diffusion-tensor tractography validation with physical phantoms
Policy memo on AI algorithm change control in cleared devices
Portable low-field MRI coil design for battlefield triage
Optoacoustic imaging probe for vascular plaque characterization
Grant proposal for carbon-neutral MRI facility design
White paper on bias mitigation in AI mammography tools
Podcast interviewing FDA reviewers on imaging-AI submissions
See deeper, diagnose sooner with UIUC Biomedical Imaging.
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