Adaptive compounding speckle-noise-reduction filter for optical coherence tomography images

Area of Science:

• Biomedical Imaging
• Medical Image Analysis
• Optical Coherence Tomography

Background:

• Speckle noise in optical coherence tomography (OCT) images degrades image contrast and obscures microstructural details.
• This noise reduction is critical for accurate tissue morphology assessment and clinical diagnosis.

Purpose of the Study:

• To develop and evaluate a novel speckle noise reduction method for OCT volumes.
• To improve the diagnostic capabilities of OCT imaging by enhancing image quality.

Main Methods:

• A speckle noise reduction technique combining adaptive-noise wavelet thresholding and wavelet compounding.
• Application to multiple frames from consecutive positions within OCT volumes.
• Utilizing wavelet representation of speckle statistics derived from homogeneous regions.

Main Results:

• The proposed method demonstrated superior performance in noise suppression and structural information preservation compared to state-of-the-art techniques.
• Quantitative evaluation using four metrics across diverse dermatological and retinal OCT datasets confirmed effectiveness.
• Successful application to clinical dermatological OCT volumes and public retinal spectral-domain OCT data.

Conclusions:

• The developed OCT denoising technique effectively reduces speckle noise across various imaging settings and noise conditions.
• This method has the potential to significantly improve OCT image quality for enhanced clinical diagnosis.
• The technique offers adaptability to different OCT modalities and clinical applications.