Quantifying particle concentration via AI-enhanced optical coherence tomography

Area of Science:

• Nanotechnology
• Biomedical Engineering
• Optical Physics

Background:

• Accurate nanoparticle quantification is crucial for nanotechnology and biomedical applications.
• Existing methods for quantifying nanoparticles in solution face limitations in efficiency and robustness.
• Gold nanorods are widely used nanoparticles with significant light-scattering properties.

Purpose of the Study:

• To develop a robust method for quantifying the number of nanoparticles in solution.
• To utilize optical coherence tomography (OCT) for nanoparticle counting.
• To enhance OCT-based quantification using artificial intelligence (AI).

Main Methods:

• Employing optical coherence tomography (OCT) to image nanoparticle solutions.
• Developing AI-enhanced image processing algorithms for OCT data.
• Quantifying gold nanorods as a model nanoparticle system.

Main Results:

• Demonstrated the feasibility of using OCT for nanoparticle quantification.
• Achieved improved accuracy and robustness in nanoparticle counting through AI enhancement.
• Successfully quantified gold nanorods in solution.

Conclusions:

• OCT, enhanced with AI, offers a promising approach for accurate nanoparticle quantification.
• This method can advance research in nanotechnology and nanomedicine.
• The developed technique addresses limitations in current nanoparticle measurement techniques.