Biomedical imaging, autonomous vehicle sensors may get boost from AI designed for physical signals
Peer-Reviewed Publication
Updates every hour. Last Updated: 19-Oct-2026 20:16 ET (20-Oct-2026 00:16 GMT/UTC)
A research team led by UCLA and the University of Rochester has demonstrated a promising evolution of an imaging system designed to capture details within “complex media,” which scatter light, from depicting structures inside body tissue to seeing obstacles through heavy fog. The system uses physics-based machine learning to improve upon an existing imaging technique.
In tests with standard calibration images obscured by complex media, the new system more than doubled the signal-to-noise ratio compared to a previous generation of the technology. The system also created images in close to real time — thousandths of a second.
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