Sub2Full: split spectrum to boost OCT despeckling without clean data

Understand

Optical coherence tomography (OCT) suffers from speckle noise, causing the deterioration of image quality, especially in high-resolution modalities like visible light OCT (vis-OCT).

• The potential of conventional supervised deep learning denoising methods is limited by the difficulty of obtaining clean data.
• Here, we proposed an innovative self-supervised strategy called Sub2Full (S2F) for OCT despeckling without clean data.
• This approach works by acquiring two repeated B-scans, splitting the spectrum of the first repeat as a low-resolution input, and utilizing the full spectrum of the second repeat as the high-resolution target.