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

CORC > 光电技术研究所 > 中国科学院光电技术研究所 > 自适应光学技术研究室（八室）

	Dual-wavelength retinal images denoising algorithm for improving the accuracy of oxygen saturation calculation
	Xian, Yong-Li 1,2,3,4; Dai, Yun 1,3; Gao, Chun-Ming 2; Du, Rui 1,3
刊名	Journal of Biomedical Optics
	2017
卷号	22 期号:1 页码:016004
关键词	Gaussian noise (electronic) - Hemoglobin oxygen saturation - Image analysis - Image matching - Image processing - Image segmentation - Ophthalmology - Optical data processing - Quality control - Sulfur dioxide
ISSN号	1083-3668
英文摘要	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. SO2is 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 SO2calculation accuracy. The aforementioned problem remains to be addressed. The purpose of this study was to improve image quality and SO2calculation 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. © 2016 The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its.
语种	英语
内容类型	期刊论文
源URL	[http://ir.ioe.ac.cn/handle/181551/8822]
专题	光电技术研究所_自适应光学技术研究室（八室）
作者单位	1.Chinese Academy of Sciences, Key Laboratory of Adaptive Optics, No. 1 Guangdian Avenue, Shuangliu, Chengdu; 610209, China; 2.University of Electronic Science and Technology of China, School of Optoelectronic Information, N. Jianshe Road, Chengdu; 610054, China; 3.Chinese Academy of Sciences, Institute of Optics and Electronics, No. 1 Guangdian Avenue, Shuangliu, Chengdu; 610209, China; 4.University of Chinese Academy of Sciences, No. 19, Yuquan Road, Shijingshan, Beijing; 100049, China
推荐引用方式 GB/T 7714	Xian, Yong-Li,Dai, Yun,Gao, Chun-Ming,et al. Dual-wavelength retinal images denoising algorithm for improving the accuracy of oxygen saturation calculation[J]. Journal of Biomedical Optics,2017,22(1):016004.
APA	Xian, Yong-Li,Dai, Yun,Gao, Chun-Ming,&Du, Rui.(2017).Dual-wavelength retinal images denoising algorithm for improving the accuracy of oxygen saturation calculation.Journal of Biomedical Optics,22(1),016004.
MLA	Xian, Yong-Li,et al."Dual-wavelength retinal images denoising algorithm for improving the accuracy of oxygen saturation calculation".Journal of Biomedical Optics 22.1(2017):016004.