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Department自适应光学技术研究室(八室)
Multi-mode images denoising algorithm for further improving the accuracy of oxygen saturation calculation in the retinal oximetry
Xian, Yongli1,2,3,4; Dai, Yun1,3
Source Publication2017 3rd IEEE International Conference on Computer and Communications, ICCC 2017
Pages1861-1867
2018-03-22
Language英语
DOI10.1109/CompComm.2017.8322861
Indexed ByEi
EI Accession Number20182905552714
SubtypeC
AbstractImage noise can dramatically affect image processing and hemoglobin oxygen saturation (SO2) calculation accuracy in non-invasive retinal oximetry. Recently, the denoising algorithm based on Variance stabilizing transform (VST) and dual domain filter (DDID) has been proposed to address this issue by our lab. Actually, dual-wavelength retinal images belong to multi-mode images, in order to maximize the use of complementary information at the edges of dual-wavelength images and further reduce the calculation error of SO2, we improve the previous algorithm. Firstly, noise parameters were also estimated by mixed Poisson-Gaussian (MPG) noise model. Secondly, a novel MPG denoising algorithm which we called VST+CDDID was proposed based on VST and cross dual domain filter. To evaluate the proposed algorithm, both simulative and real experiments have been carried out and the results show that the proposed method can effectively remove MPG noise and preserve edge details. Compared with VST+DDID, the proposed method shows great advantage in terms of PSNR, SSIM and visual quality. The following simulation and analysis indicate that the images denoised by VST+CDDID can provide more accurate grayscale values than the images denoised by VST+DDID for retinal oximetry. © 2017 IEEE.
KeywordEdge detection Hemoglobin oxygen saturation Image denoising Ophthalmology Oxygen
EI KeywordsEdge detection ; Hemoglobin oxygen saturation ; Image denoising ; Ophthalmology ; Oxygen
Conference Name3rd IEEE International Conference on Computer and Communications, ICCC 2017
Conference DateDecember 13, 2017 - December 16, 2017
Conference PlaceChengdu, China
EI Classification Number461.2 Biological Materials and Tissue Engineering ; 461.6 Medicine and Pharmacology ; 716.1 Information Theory and Signal Processing ; 804 Chemical Products Generally
Citation statistics
Document Type会议论文
Identifierhttp://ir.ioe.ac.cn/handle/181551/9120
Collection自适应光学技术研究室(八室)
Affiliation1.Chinese Academy of Sciences, Key Laboratory of Adaptive Optics, Chengdu, China;
2.School of Optoelectronic Information, University of Electronic Science and Technology of China, Chengdu, China;
3.Chinese Academy of Sciences, Institute of Optics and Electronics, Chengdu, China;
4.University of Chinese Academy of Sciences, Chengdu, China
Recommended Citation
GB/T 7714
Xian, Yongli,Dai, Yun. Multi-mode images denoising algorithm for further improving the accuracy of oxygen saturation calculation in the retinal oximetry[C],2018:1861-1867.
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