| 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 Publication | 2017 3rd IEEE International Conference on Computer and Communications, ICCC 2017 |
| Pages | 1861-1867 |
| 2018-03-22 | |
| Language | 英语 |
| DOI | 10.1109/CompComm.2017.8322861 |
| Indexed By | Ei |
| EI Accession Number | 20182905552714 |
| Subtype | C |
| Abstract | Image 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. |
| Keyword | Edge detection Hemoglobin oxygen saturation Image denoising Ophthalmology Oxygen |
| EI Keywords | Edge detection ; Hemoglobin oxygen saturation ; Image denoising ; Ophthalmology ; Oxygen |
| Conference Name | 3rd IEEE International Conference on Computer and Communications, ICCC 2017 |
| Conference Date | December 13, 2017 - December 16, 2017 |
| Conference Place | Chengdu, China |
| EI Classification Number | 461.2 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 |
| Identifier | http://ir.ioe.ac.cn/handle/181551/9120 |
| Collection | 自适应光学技术研究室（八室） |
| Affiliation | 1.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. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| 2018-2143.pdf（490KB） | 会议论文 | 开放获取 | CC BY-NC-SA | Application Full Text | ||
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