Imaging dynamics beneath turbid media via parallelized single-photon detection

TL;DR

This paper presents a novel method using single-photon detection and deep learning to noninvasively image and reconstruct dynamic scattering events beneath turbid media, achieving millimeter-scale resolution at depths up to 8 mm.

Contribution

It introduces a new experimental setup combining SPAD array imaging with neural networks for deep-tissue video reconstruction of decorrelation dynamics.

Findings

Successfully reconstructed transient events up to 8 mm deep

Achieved millimeter-scale spatial resolution

Extended method to monitor flow speed in phantom vessels

Abstract

Noninvasive optical imaging through dynamic scattering media has numerous important biomedical applications but still remains a challenging task. While standard diffuse imaging methods measure optical absorption or fluorescent emission, it is also well-established that the temporal correlation of scattered coherent light diffuses through tissue much like optical intensity. Few works to date, however, have aimed to experimentally measure and process such temporal correlation data to demonstrate deep-tissue video reconstruction of decorrelation dynamics. In this work, we utilize a single-photon avalanche diode (SPAD) array camera to simultaneously monitor the temporal dynamics of speckle fluctuations at the single-photon level from 12 different phantom tissue surface locations delivered via a customized fiber bundle array. We then apply a deep neural network to convert the acquired single-photon measurements into video of scattering dynamics beneath rapidly decorrelating tissue phantoms. We demonstrate the ability to reconstruct images of transient (0.1-0.4s) dynamic events occurring up to 8 mm beneath a decorrelating tissue phantom with millimeter-scale resolution, and highlight how our model can flexibly extend to monitor flow speed within buried phantom vessels.