Universal digital filtering for denoising volumetric retinal OCT and OCT angiography in 3D shearlet domain

TL;DR

This paper introduces a universal 3D shearlet-based digital filtering method that effectively denoises both OCT and OCTA volumetric retinal images, outperforming existing techniques by leveraging the distinct features in shearlet domain.

Contribution

The novel approach applies 3D shearlet decomposition for simultaneous denoising of OCT and OCTA, addressing limitations of prior filters that only targeted OCT.

Findings

Outperforms state-of-the-art OCT and OCTA denoising methods.

3D shearlet filtering surpasses 2D in denoising quality.

Better representation of retinal layer edges and vasculature.

Abstract

Retinal optical coherence tomography (OCT) and OCT angiography (OCTA) suffer from the degeneration of image quality due to speckle noise and bulk-motion noise, respectively. Because the cross-sectional retina has distinct features in OCT and OCTA B-scans, existing digital filters that can denoise OCT efficiently are unable to handle the bulk-motion noise in OCTA. In this Letter, we propose a universal digital filtering approach that is capable of minimizing both types of noise. Considering the retinal capillaries in OCTA are hard to differentiate in B-scans while having distinct curvilinear structures in 3D volumes, we decompose the volumetric OCT and OCTA data with 3D shearlets thus efficiently separate the retinal tissue and vessels from the noise in this transform domain. Compared with wavelets and curvelets, the shearlets provide better representation of the layer edges in OCT and the vasculature in OCTA. Qualitative and quantitative results show the proposed method outperforms the state-of-the-art OCT and OCTA denoising methods. Besides, the superiority of 3D denoising is demonstrated by comparing the 3D shearlet filtering with its 2D counterpart.