Automated noise estimation in polarization-sensitive optical coherence tomography.

Area of Science:

• Biomedical Optics
• Medical Imaging Technology
• Optical Physics

Background:

• Accurate signal noise floor determination is essential for advanced signal reconstruction in polarization-sensitive optical coherence tomography (PS-OCT).
• Existing methods for noise floor evaluation in PS-OCT are often subjective and impractical for routine use.
• Noise floor estimation directly impacts the quality and reliability of quantitative PS-OCT data.

Purpose of the Study:

• To develop and validate an automated, objective method for estimating the noise floor in PS-OCT.
• To improve the accuracy and practicality of noise floor determination for PS-OCT signal processing.
• To establish a robust noise estimation technique applicable across various PS-OCT systems and in vivo imaging.

Main Methods:

• Utilizing the degree of polarization uniformity as a key parameter for noise assessment.
• Incorporating known speckle intensity statistics to model the noise floor.
• Developing an automated algorithm for noise floor estimation based on polarization and intensity data.
• Validating the method through phantom experiments and in vivo imaging studies.

Main Results:

• The proposed method accurately models and estimates the PS-OCT noise floor automatically.
• The noise estimation technique demonstrates robustness across different imaging systems.
• Successful application of the method in various in vivo imaging scenarios.
• Objective and reproducible noise floor quantification achieved.

Conclusions:

• The developed automated method provides a practical and objective solution for PS-OCT noise floor estimation.
• This technique enhances the reliability of signal reconstruction and quantitative analysis in PS-OCT.
• The findings support the broader adoption of accurate noise floor assessment in PS-OCT applications.