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Related Experiment Video

Updated: May 7, 2026

Live Cell Imaging of F-actin Dynamics via Fluorescent Speckle Microscopy FSM

Live Cell Imaging of F-actin Dynamics via Fluorescent Speckle Microscopy FSM

Published on: August 5, 2009

Probing diffusive media through speckle differencing.

Muralidhar Madabhushi Balaji^1,2, Danyal Ahsanullah¹, Prasanna Rangarajan^1,3

¹Electrical and Computer Engineering, Lyle School of Engineering, Southern Methodist University, Dallas, Texas 75205, USA.

Biomedical Optics Express

|September 19, 2024

Summary

This summary is machine-generated.

This study detects inhomogeneities in scattering media using temporal speckle differences. A novel neuromorphic sensor approach simplifies detection and reduces data, capturing only differential 1-bit spike information.

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Last Updated: May 7, 2026

Live Cell Imaging of F-actin Dynamics via Fluorescent Speckle Microscopy FSM

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Published on: August 5, 2009

Preparation of Mica Supported Lipid Bilayers for High Resolution Optical Microscopy Imaging

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Published on: June 7, 2014

Spectral Reflectometric Microscopy on Myelinated Axons In Situ

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Published on: July 2, 2018

Area of Science:

Optics and Photonics
Biophysics
Sensor Technology

Background:

Speckle patterns from light-matter interaction reveal internal medium properties.
Speckle fluctuations are caused by laser frequency tuning or dynamic scatterer motion.
Detecting inhomogeneities in scattering media is crucial for various applications.

Purpose of the Study:

To detect embedded inhomogeneities in static and dynamic scattering media.
To introduce a novel bio-inspired neuromorphic sensing approach for speckle analysis.
To simplify optical/electronic design and reduce data throughput for inhomogeneity detection.

Main Methods:

Probing static and dynamic scattering media with coherent light.
Analyzing the statistical distribution of temporal speckle differences.
Utilizing bio-inspired neuromorphic sensors to capture differential information as 1-bit spikes.

Main Results:

Successfully detected embedded inhomogeneities using temporal speckle differences.
Demonstrated the first experimental results of inhomogeneity detection with neuromorphic sensors.
Neuromorphic approach significantly reduced data throughput by capturing only differential information.

Conclusions:

Temporal speckle differencing is an effective method for detecting inhomogeneities.
Neuromorphic sensors offer a simplified and efficient platform for speckle-based sensing.
This work paves the way for advanced, low-data-rate optical sensing systems.