Imaging Dynamics Beneath Turbid Media via Parallelized Single‐Photon Detection

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, a single‐photon avalanche diode array camera is utilized 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. Then a deep neural network is applied to convert the acquired single‐photon measurements into video of scattering dynamics beneath rapidly decorrelating tissue phantoms. The ability to reconstruct images of transient (0.1–0.4 s) dynamic events occurring up to 8 mm beneath a decorrelating tissue phantom with millimeter‐scale resolution is demonstrated, and it is highlighted how the model can flexibly extend to monitor flow speed within buried phantom vessels.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jun 24, 2022
Source ID
10.1002/advs.202201885

Entities

People

  • Edouard Berrocal
  • Haoqian Wang
  • Joakim Jönsson
  • Kevin C. Zhou
  • Lucas Kreiß
  • Pavan Chandra Konda
  • Qionghai Dai
  • Roarke Horstmeyer
  • Ruobing Qian
  • Shiqi Xu
  • Wenhui Liu
  • Xi Yang

Organizations

  • Air Force Research Laboratory
  • Duke University
  • Friedrich-Alexander-Universität Erlangen-Nürnberg
  • Hartwell Foundation
  • Lund University
  • National Institute of Neurological Disorders and Stroke
  • Tsinghua University

Tags

Fields of Study

  • Physics

Readers

  • Computer Vision.
  • Nanoscale Plasmonic Nanotechnology
  • Optical Physics and Photonics.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Biotechnology