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

Jianlong Yang, Yan Hu, Liyang Fang, Jun Cheng, Jiang Liu

Research output: Journal PublicationArticlepeer-review

13 Citations (Scopus)


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 that 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 separating 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. Also, the superiority of 3D denoising is demonstrated by comparing the 3D shearlet filtering with its 2D counterpart.

Original languageEnglish
Pages (from-to)694-697
Number of pages4
JournalOptics Letters
Issue number3
Publication statusPublished - 1 Feb 2020
Externally publishedYes

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics


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