Optimization of the split-spectrum amplitude-decorrelation angiography algorithm on a spectral optical coherence...

Area of Science:

• Ophthalmology
• Biomedical Engineering
• Medical Imaging

Background:

• Spectral optical coherence tomography (SOCT) is crucial for retinal imaging.
• Amplitude-decorrelation angiography (ADA) methods require optimization for enhanced flow detection.

Purpose of the Study:

• To optimize the split-spectrum amplitude-decorrelation angiography (SSADA) algorithm for SOCT systems.
• To improve the detection of retinal microvascular flow and reduce variability in vessel density quantification.

Main Methods:

• The SSADA algorithm was optimized using a flow phantom by adjusting spectrum splitting parameters.
• Optimization focused on maximizing the decorrelation signal-to-noise ratio.
• The optimized algorithm was validated using en face retinal angiograms.

Main Results:

• Optimization of the SSADA algorithm significantly improved flow detection sensitivity.
• The enhanced algorithm increased the detection of retinal microvascular flow.
• Quantified vessel density in OCT retinal angiograms showed decreased variability in healthy subjects.

Conclusions:

• The optimized SSADA algorithm enhances microvascular flow visualization in SOCT retinal imaging.
• This advancement offers improved diagnostic capabilities for retinal vascular diseases.
• Reduced variability in vessel density measurements aids in more reliable clinical assessments.