Single-sensor and real-time ultrasonic imaging using an AI-driven disordered metasurface

TL;DR

This paper introduces an AI-enhanced disordered ultrasonic metasurface that enables real-time, low-cost imaging with a single sensor, overcoming traditional limitations of spatial scanning and multi-mode switching.

Contribution

It combines disordered metasurfaces with AI decoding to achieve real-time ultrasonic imaging using only one fixed sensor, simplifying design and reducing costs.

Findings

Successful demonstration of single-sensor ultrasonic imaging

Real-time recognition of complex objects achieved

Extension potential to 3D imaging

Abstract

Non-destructive testing and medical diagnostic techniques using ultrasound has become indispensable in evaluating the state of materials or imaging the internal human body, respectively. To conduct spatially resolved high-quality observations, conventionally, sophisticated phased arrays are used both at the emitting and receiving ends of the setup. In comparison, single-sensor imaging techniques offer significant benefits including compact physical dimensions and reduced manufacturing expenses. However, recent advances such as compressive sensing have shown that this improvement comes at the cost of additional time-consuming dynamic spatial scanning or multi-mode mask switching, which severely hinders the quest for real-time imaging. Consequently, real-time single-sensor imaging, at low cost and simple design, still represents a demanding and largely unresolved challenge till this day. Here, we bestow on ultrasonic metasurface with both disorder and artificial intelligence (AI). The former ensures strong dispersion and highly complex scattering to encode the spatial information into frequency spectra at an arbitrary location, while the latter is used to decode instantaneously the amplitude and spectral component of the sample under investigation. Thus, thanks to this symbiosis, we demonstrate that a single fixed sensor suffices to recognize complex ultrasonic objects through the random scattered field from an unpretentious metasurface, which enables real-time and low-cost imaging, easily extendable to 3D.