Transient motion classification through turbid volumes via parallelized single-photon detection and deep contrastive embedding

by   Shiqi Xu, et al.

Fast noninvasive probing of spatially varying decorrelating events, such as cerebral blood flow beneath the human skull, is an essential task in various scientific and clinical settings. One of the primary optical techniques used is diffuse correlation spectroscopy (DCS), whose classical implementation uses a single or few single-photon detectors, resulting in poor spatial localization accuracy and relatively low temporal resolution. Here, we propose a technique termed Classifying Rapid decorrelation Events via Parallelized single photon dEtection (CREPE), a new form of DCS that can probe and classify different decorrelating movements hidden underneath turbid volume with high sensitivity using parallelized speckle detection from a 32×32 pixel SPAD array. We evaluate our setup by classifying different spatiotemporal-decorrelating patterns hidden beneath a 5mm tissue-like phantom made with rapidly decorrelating dynamic scattering media. Twelve multi-mode fibers are used to collect scattered light from different positions on the surface of the tissue phantom. To validate our setup, we generate perturbed decorrelation patterns by both a digital micromirror device (DMD) modulated at multi-kilo-hertz rates, as well as a vessel phantom containing flowing fluid. Along with a deep contrastive learning algorithm that outperforms classic unsupervised learning methods, we demonstrate our approach can accurately detect and classify different transient decorrelation events (happening in 0.1-0.4s) underneath turbid scattering media, without any data labeling. This has the potential to be applied to noninvasively monitor deep tissue motion patterns, for example identifying normal or abnormal cerebral blood flow events, at multi-Hertz rates within a compact and static detection probe.


page 1

page 4

page 7

page 8

page 9


Imaging dynamics beneath turbid media via parallelized single-photon detection

Noninvasive optical imaging through dynamic scattering media has numerou...

Image-based deep learning for classification of noise transients in gravitational wave detectors

The detection of gravitational waves has inaugurated the era of gravitat...

A novel optical needle probe for deep learning-based tissue elasticity characterization

The distinction between malignant and benign tumors is essential to the ...

Deformation-Aware Robotic 3D Ultrasound

Tissue deformation in ultrasound (US) imaging leads to geometrical error...

Probe-based Rapid Hybrid Hyperspectral and Tissue Surface Imaging Aided by Fully Convolutional Networks

Tissue surface shape and reflectance spectra provide rich intra-operativ...

Testing a Drop of Liquid Using Smartphone LiDAR

We present the first system to determine fluid properties using the LiDA...

Please sign up or login with your details

Forgot password? Click here to reset