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Mixed multiscale BM4D for three-dimensional optical coherence tomography denoising.
- Source :
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Computers in biology and medicine [Comput Biol Med] 2023 Mar; Vol. 155, pp. 106658. Date of Electronic Publication: 2023 Feb 13. - Publication Year :
- 2023
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Abstract
- A multiscale extension for the well-known block matching and 4D filtering (BM4D) method is proposed by analyzing and extending the wavelet subbands denoising method in such a way that the proposed method avoids directly denoising detail subbands, which considerably simplifies the computations and makes the multiscale processing feasible in 3D. To this end, we first derive the multiscale construction method in 2D and propose multiscale extensions for three 2D natural image denoising methods. Then, the derivation is extended to 3D by proposing mixed multiscale BM4D (mmBM4D) for optical coherence tomography (OCT) image denoising. We tested mmBM4D on three public OCT datasets captured by various imaging devices. The experiments revealed that mmBM4D significantly outperforms its original counterpart and performs on par with the state-of-the-art OCT denoising methods. In terms of peak-signal-to-noise-ratio (PSNR), mmBM4D surpasses the original BM4D by more than 0.68 decibels over the first dataset. In the second and third datasets, significant improvements in the mean to standard deviation ratio, contrast to noise ratio, and equivalent number of looks were achieved. Furthermore, on the downstream task of retinal layer segmentation, the layer quality preservation of the compared OCT denoising methods is evaluated.<br />Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2023. Published by Elsevier Ltd.)
Details
- Language :
- English
- ISSN :
- 1879-0534
- Volume :
- 155
- Database :
- MEDLINE
- Journal :
- Computers in biology and medicine
- Publication Type :
- Academic Journal
- Accession number :
- 36827787
- Full Text :
- https://doi.org/10.1016/j.compbiomed.2023.106658