# Imaging dynamics beneath turbid media via parallelized single-photon detection

arXiv: https://arxiv.org/abs/2107.01422 · HTML: https://mlsanity.com/paper/2107.01422/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 85 references that are in the map.
- First posted on arXiv 3 Jul 2021.

## Builds on (most cited first, 8 of 8)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Prototypical Networks for Few-shot Learning](https://mlsanity.com/paper/1703.05175/) (2017)
- [Stochastic Gradient Descent as Approximate Bayesian Inference](https://mlsanity.com/paper/1704.04289/) (2017)
- [Image reconstruction by domain transform manifold learning](https://mlsanity.com/paper/1704.08841/) (2017)
- [A megapixel time-gated SPAD image sensor for 2D and 3D imaging applications](https://mlsanity.com/paper/1912.12910/) (2019)
- [Deep speckle correlation: a deep learning approach towards scalable imaging through scattering media](https://mlsanity.com/paper/1806.04139/) (2018)
- [High Resolution, Deep Imaging Using Confocal Time-of-flight Diffuse Optical Tomography](https://mlsanity.com/paper/2101.11680/) (2021)
- [Wavefront shaping in complex media at 350 KHz with a 1D-to-2D transform](https://mlsanity.com/paper/1808.09025/) (2018)

## Built on by (most cited first, 1 of 1)

- [Transient motion classification through turbid volumes via parallelized single-photon detection and deep contrastive embedding](https://mlsanity.com/paper/2204.01733/) (2022)

## Abstract (arXiv)

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.