Dual-wavelength retinal images denoising algorithm for improving the accuracy of oxygen saturation calculation

Yong-Li Xian; Yun Dai; Chun-Ming Gao; Rui Du

doi:10.1117/1.JBO.22.1.016004

5 January 2017 Dual-wavelength retinal images denoising algorithm for improving the accuracy of oxygen saturation calculation

Yong-Li Xian, Yun Dai, Chun-Ming Gao, Rui Du

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Journal of Biomedical Optics, Vol. 22, Issue 1, 016004 (January 2017). https://doi.org/10.1117/1.JBO.22.1.016004

Abstract

Noninvasive measurement of hemoglobin oxygen saturation (SO2) in retinal vessels is based on spectrophotometry and spectral absorption characteristics of tissue. Retinal images at 570 and 600 nm are simultaneously captured by dual-wavelength retinal oximetry based on fundus camera. SO2 is finally measured after vessel segmentation, image registration, and calculation of optical density ratio of two images. However, image noise can dramatically affect subsequent image processing and SO2 calculation accuracy. The aforementioned problem remains to be addressed. The purpose of this study was to improve image quality and SO2 calculation accuracy by noise analysis and denoising algorithm for dual-wavelength images. First, noise parameters were estimated by mixed Poisson–Gaussian (MPG) noise model. Second, an MPG denoising algorithm which we called variance stabilizing transform (VST) + dual-domain image denoising (DDID) was proposed based on VST and improved dual-domain filter. The results show that VST + DDID is able to effectively remove MPG noise and preserve image edge details. VST + DDID is better than VST + block-matching and three-dimensional filtering, especially in preserving low-contrast details. The following simulation and analysis indicate that MPG noise in the retinal images can lead to erroneously low measurement for SO2, and the denoised images can provide more accurate grayscale values for retinal oximetry.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Yong-Li Xian, Yun Dai, Chun-Ming Gao, and Rui Du "Dual-wavelength retinal images denoising algorithm for improving the accuracy of oxygen saturation calculation," Journal of Biomedical Optics 22(1), 016004 (5 January 2017). https://doi.org/10.1117/1.JBO.22.1.016004

Received: 12 September 2016; Accepted: 15 December 2016; Published: 5 January 2017

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