Computational adaptive optics in phase-unstable optical coherence tomography.

Area of Science:

• Biomedical optics
• Optical engineering
• Medical imaging

Background:

• Optical coherence tomography (OCT) is a powerful imaging modality.
• Aberrations and phase instability in OCT systems degrade image quality and limit imaging depth.
• Existing aberration correction methods often require hardware modifications or are incompatible with phase-unstable systems.

Purpose of the Study:

• To present a novel computational method, SHARP (Self-Heuristic Aberration Reconstruction Protocol), for correcting x-y-separable aberrations in OCT.
• To demonstrate the effectiveness of SHARP in phase-unstable OCT systems without requiring hardware changes.
• To evaluate the performance of SHARP in improving image quality for in vivo and ex vivo OCT data.

Main Methods:

• SHARP utilizes computational adaptive optics and numerical phase correction.
• The method leverages the principle that local phase stability is sufficient for aberration deconvolution.
• SHARP was tested on a raster-scan polygon-laser OCT system with significant phase-jitter noise.

Main Results:

• SHARP successfully corrected aberrations and achieved refocusing up to 4 times the Rayleigh range in a phase-unstable OCT system.
• Significant image quality enhancement was observed in both in vivo endoscopic and ex vivo anterior segment OCT data.
• Combining SHARP with a resolution-preserving despeckling technique (TNode) further improved image quality.

Conclusions:

• SHARP offers a hardware-independent solution for correcting optical aberrations in OCT systems, particularly those with phase instability.
• The computational approach enables enhanced imaging depth and quality in challenging OCT applications.
• SHARP shows promise for improving diagnostic capabilities in various OCT-based imaging scenarios.