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Terahertz pulsed imaging in vivo: measurements and processing methods.

Edward P J Parrott¹, Stanley M Y Sy, Thierry Blu

¹Chinese University of Hong Kong, Department of Electronic Engineering, Shatin, Hong Kong.

Journal of Biomedical Optics

|October 28, 2011

Summary

New data processing algorithms enhance terahertz (THz) handheld probe accuracy for biological samples. These methods improve the determination of spectroscopic and time-domain properties, particularly for in vivo human skin measurements.

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Area of Science:

Biomedical Engineering
Spectroscopy
Data Science

Background:

Terahertz (THz) imaging offers non-ionizing, non-destructive analysis capabilities.
Accurate data acquisition from handheld THz probes is crucial for in vivo applications.
Existing methods for analyzing THz data from biological tissues have limitations.

Purpose of the Study:

To develop and validate advanced data processing algorithms for THz handheld probe datasets.
To enhance the accuracy of spectroscopic and time-domain property extraction from biological samples.
To demonstrate the utility of these algorithms using in vivo human skin measurements.

Main Methods:

Baseline subtraction algorithm.
Sample impulse response extraction techniques: double Gaussian inverse filtering, frequency-wavelet domain deconvolution, and sparse deconvolution.
Application of algorithms to in vivo human skin measurements in reflection geometry.

Main Results:

The developed algorithms significantly improve the accuracy of THz data analysis.
Demonstrated enhanced determination of spectroscopic and time-domain properties compared to previous methods.
Successful application to differentiate THz impulse responses across various human skin locations.

Conclusions:

The presented data processing algorithms are effective in improving THz handheld probe measurement accuracy.
These techniques enable more precise characterization of biological sample properties.
The study highlights the potential of advanced algorithms for in vivo THz applications.