Self-fusion for OCT Noise Reduction

Overview

Journal Proc SPIE Int Soc Opt Eng

Date 2021 Dec 7

PMID 34873356

Citations 7

Authors

Ipek Oguz

Joseph D Malone

Yigit Atay

Yuankai K Tao

Affiliations

Soon will be listed here.

Abstract

Reducing speckle noise is an important task for improving visual and automated assessment of retinal OCT images. Traditional image/signal processing methods only offer moderate speckle reduction; deep learning methods can be more effective but require substantial training data, which may not be readily available. We present a novel self-fusion method that offers effective speckle reduction comparable to deep learning methods, but without any external training data. We present qualitative and quantitative results in a variety of datasets from fovea and optic nerve head regions, with varying SNR values for input images.

Citing Articles

Probabilistic volumetric speckle suppression in OCT using deep learning.

Chintada B, Ruiz-Lopera S, Restrepo R, Bouma B, Villiger M, Uribe-Patarroyo N Biomed Opt Express. 2024; 15(8):4453-4469.

PMID: 39346991 PMC: 11427188. DOI: 10.1364/BOE.523716.

Recurrent Self Fusion: Iterative Denoising for Consistent Retinal OCT Segmentation.

Wei S, Liu Y, Bian Z, Wang Y, Zuo L, Calabresi P Ophthalmic Med Image Anal (2023). 2024; 14096:42-51.

PMID: 38318463 PMC: 10840975. DOI: 10.1007/978-3-031-44013-7_5.

Probabilistic volumetric speckle suppression in OCT using deep learning.

Chintada B, Ruiz-Lopera S, Restrepo R, Bouma B, Villiger M, Uribe-Patarroyo N ArXiv. 2023; .

PMID: 38106457 PMC: 10723542.

MURIN: Multimodal Retinal Imaging and Navigated-laser-delivery for dynamic and longitudinal tracking of photodamage in murine models.

Rico-Jimenez J, Jovanovic J, Nolen S, Malone J, Rao G, Levine E Front Ophthalmol (Lausanne). 2023; 3.

PMID: 37275441 PMC: 10238074. DOI: 10.3389/fopht.2023.1141070.

Retinal OCT Denoising with Pseudo-Multimodal Fusion Network.

Hu D, Malone J, Atay Y, Tao Y, Oguz I Ophthalmic Med Image Anal (2020). 2022; 12069:125-135.

PMID: 35775870 PMC: 9241435. DOI: 10.1007/978-3-030-63419-3_13.

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