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摘要: 光学相干层析成像(OCT)由于具有微米级高分辨率、非接触式成像以及瞬时性等特点，成为临床医学领域的研究热点，近些年得到迅速的发展，取得诸多进展与突破。本文简述了OCT技术在眼科医学中的各类应用及发展现状，分类讨论了OCT图像在空域和频域中的降噪方法，并重点总结了OCT眼前节和视网膜图像中各层组织的精确定位分层方法。其中深入分析了基于灰度值搜索方法、活动轮廓模型、图论和模式识别等分层方法，并针对现有分层方法的优缺点以及存在的问题展开深入讨论，提出相应的解决方法和优化方案。对眼科相关疾病的临床诊断指标分析评价，根据眼科临床医学需求和OCT图像处理现状，对未来OCT图像处理的发展趋势和发展水平做进一步讨论和分析。Abstract: Optical coherence tomography(OCT) has become a hot research topic in the field of clinical medicine due to its features including micron-level high resolution, non-invasive imaging and instantaneity, which has developed rapidly and made much progress and break throughs in recent years. In this paper we briefly review the applications of OCT in ophthalmology, discuss the methods of speckle noise reduction in the spatial and frequency domains of OCT images, and summarize the precise positioning and stratification method of each layer of tissue in the OCT anterior segment and retina image. The advantages and disadvantages of the segmentation methods based on gray value search, active contour model, graph and pattern recognition algorithms are analyzed and compared. In addition, the existing problems with segmentation methods are discussed and the corresponding solutions and feasible optimization schemes are proposed. Analysis and evaluation of clinical diagnostic indicators of ophthalmic diseases are discussed. According to the needs in ophthalmology and the current status of OCT image processing, the development trends and level of OCT image processing are discussed and analyzed.
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Key words:
- optical coherence tomography /
- anterior segment /
- retinal image /
- image segmentation
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图 1 (a) 眼前节OCT图像；(b)视网膜OCT图像
Figure 1. (a)OCT of the anterior segment; (b)retinal OCT image
图 2 各类视网膜病变的OCT图像(a)健康视网膜黄斑中心凹(b)黄斑裂洞(c)黄斑水肿(d)年龄相关黄斑变性(e)中央浆液脉络膜视网膜病(f)增殖性糖尿病视网膜病变
Figure 2. OCT images of various retinal diseases. (a)healthy macular fovea; (b)macular hole; (c) macular edema; (d)age-related macular degeneration; (e)central serous retinopathy; (f)proliferative diabetic retinopathy
图 5 不同例健康视网膜RPE和ILM分层结果
Figure 5. RPE and ILM stratification results of healthy retinal in different cases
图 6 Mujat等提出的基于活动轮廓的视网膜分层方法
Figure 6. Retinal stratification method based on active contour proposed by Mujat
图 7 INL层分割互补梯度示意图
Figure 7. A diagram of a complementary gradient for dividing INL boundary
图 8 使用SVM对不同病症视网膜OCT成像的分割结果. (a)健康眼; (b)年龄相关黄斑变性; (c)黄斑分离; (d)青光眼
Figure 8. Results of SVM segmentation for retinal OCT imaging of different diseases. (a)Healthy eyes; (b)age-related macular degeneration; (c)macular separation; (d)glaucoma
表 2 OCT临床诊断指标与算法效果对比
Table 2. Clinical diagnostic index of OCT and comparison of image processing effect with different algorithms
病灶名称 临床指标 检测方法 检测误差 脉络膜视网膜病 中央凹或视网膜色素上皮细胞隆起、内界膜变形 ILM层定位及厚度分割[17] 误差＜5 pixels 年龄相关黄斑变性 视网膜色素上皮细胞脱落、脉络膜毛细血管断裂、色素上皮下脉络膜毛细血管光带增强、光感受器厚度增大 灰度值搜索法测量RPE层厚度[17] 误差＞10 pixels 图论法对RPE层厚度测量[46] 测量误差(1.430±0.20) μm 通过模式识别对PRL层分割[47] 误差＜6 pixels 青光眼 视神经纤维层厚度变化；
杯盘比CDR＞0.5NFL层厚度测量[47]
视神经乳头杯盘比测量[50]误差＜6 pixels
测量误差(7.27±5.4) μm
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[1] AMBROSINI P, RUIJTERS D, NIESSEN W J, et al.. Fully automatic and real-time catheter segmentation in X-ray fluoroscopy[C]. Proceedings of the 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer, 2017: 577-585. [2] RUBIN G D, KRUPINSKI E A. Tracking eye movements during CT interpretation:inferences of reader performance and clinical competency require clinically realistic procedures for unconstrained search[J]. Radiology, 2017, 283(3):920. doi: 10.1148/radiol.2017170067 [3] PHAM C H, DUCOURNAU A, FABLET R, et al.. Brain MRI super-resolution using deep 3D convolutional networks[C]. Proceedings of the 14th International Symposium on Biomedical Imaging, IEEE, 2017: 197-200. [4] PAVLIN C J, SHERAR M D, FOSTER F S. Subsurface ultrasound microscopic imaging of the intact eye[J]. Ophthalmology, 1990, 97(2):244-250. doi: 10.1016/S0161-6420(90)32598-8 [5] PAPANAS N, ZIEGLER D. Corneal confocal microscopy:recent progress in the evaluation of diabetic neuropathy[J]. Journal of Diabetes Investigation, 2015, 6(4):381-389. doi: 10.1111/jdi.12335 [6] CHEN Y, HERZ P R, HSIUNG P L, et al.. Ultrahigh-resolution endoscopic optical coherence tomography for gastrointestinal imaging[J]. Proceedings of SPIE, 2005, 5690:4-10. doi: 10.1117/12.592609 [7] 彭诚, 张芹芹, 吴晓静, 等.谱域OCT成像系统在口腔组织检测中的应用[J].光学 精密工程, 2011, 19(8):1931-1936. http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201108030PENG CH, ZHANG Q Q, WU X J, et al.. Application of spectral domain optical coherence tomography to oral cavity tissue test[J]. Opt. Precision Eng., 2011, 19(8):1931-1936.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201108030 [8] MEN J, HUANG Y Y, SOLANKI J, et al.. Optical coherence tomography for brain imaging and developmental biology[J]. IEEE Journal of Selected Topics in Quantum Electronics, 2016, 22(4):120-132. https://www.ncbi.nlm.nih.gov/pubmed/27721647 [9] ADAMS D C, WANG Y, HARIRI L P, et al.. Advances in endoscopic optical coherence tomography catheter designs[J]. IEEE Journal of Selected Topics in Quantum Electronics, 2016, 22(3):210-221. doi: 10.1109/JSTQE.2015.2510295 [10] 孙正, 郑兰.定量光声层析成像的研究进展[J].发光学报, 2017, 38(9):1222-1232. http://d.old.wanfangdata.com.cn/Periodical/fgxb201709016SUN ZH, ZHENG L. Review on progress of quantitative photoacoustic tomography[J]. Chinese Journal of Luminescence, 2017, 38(9):1222-1232.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/fgxb201709016 [11] HUANG D, SWANSON E A, LIN C P, et al.. Optical coherence tomography[J]. Science, 1991, 254(5035):1178-1181. doi: 10.1126/science.1957169 [12] PERONA P, MALIK J. Scale-space and edge detection using anisotropic diffusion[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990, 12(7):629-639. doi: 10.1109/34.56205 [13] 王亚强, 陈波.一种改进的各向异性扩散超声图像去噪算法[J].液晶与显示, 2015, 30(2):310-316. http://d.old.wanfangdata.com.cn/Periodical/yjyxs201502020WANG Y Q, CHEN B. Improved anisotropic diffusion ultrasound image denoising algorithm[J]. Chinese Journal of Liquid Crystals and Displays, 2015, 30(2):310-316.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/yjyxs201502020 [14] OZCAN A, BILENCA A, DESJARDINS A E, et al.. Speckle reduction in optical coherence tomography images using digital filtering[J]. Journal of the Optical Society of America A, 2007, 24(7):1901-1910. doi: 10.1364/JOSAA.24.001901 [15] FERNÁNDEZ D C. Delineating fluid-filled region boundaries in optical coherence tomography images of the retina[J]. IEEE Transactions on Medical Imaging, 2005, 24(8):929-945. doi: 10.1109/TMI.2005.848655 [16] 孙延奎.光学相干层析医学图像处理及其应用[J].光学 精密工程, 2014, 22(4):1086-1104. http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201404037SUN Y K. Medical image processing techniques based on optical coherence tomography and their applications[J]. Opt. Precision Eng., 2014, 22(4):1086-1104.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201404037 [17] FABRITIUS T, MAKITA S, MIURA M, et al.. Automated segmentation of the macula by optical coherence tomography[J]. Optics Express, 2009, 17(18):15659-15669. doi: 10.1364/OE.17.015659 [18] 王立科, 张佳莹, 田磊, 等.基于光学相干层析气冲印压技术研究角膜生物力学特性[J].光学 精密工程, 2015, 23(2):325-333. http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201502002WANG L K, ZHANG J Y, TIAN L, et al.. OCT based air jet indentation for corneal biomechanical assessment[J]. Opt. Precision Eng., 2015, 23(2):325-333.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201502002 [19] IZATT J A, HEE M R, SWANSON E A, et al.. Micrometer-scale resolution imaging of the anterior eye in vivo with optical coherence tomography[J]. Archives of Ophthalmology, 1994, 112(12):1584-1589. doi: 10.1001/archopht.1994.01090240090031 [20] HEE M R, IZATT J A, SWANSON E A, et al.. Optical coherence tomography of the human retina[J]. Archives of Ophthalmology, 1995, 113(3):325-332. doi: 10.1001/archopht.1995.01100030081025 [21] SCHUMAN J S, PEDUT-KLOIZMAN T, HERTZMARK E, et al.. Reproducibility of nerve fiber layer thickness measurements using optical coherence tomography[J]. Ophthalmology, 1996, 103(11):1889-1898. doi: 10.1016/S0161-6420(96)30410-7 [22] STAURENGHI G, SADDA S, CHAKRAVARTHY U, et al.. Proposed lexicon for an atomic landmarks in normal posterior segment spectral-domain optical coherence tomography:The IN OCT consensus[J]. Ophthalmology, 2014, 121(8):1572-1578. doi: 10.1016/j.ophtha.2014.02.023 [23] AREVALO J F. Retinal Angiography and Optical Coherence Tomography[M]. New York:Springer, 2009:239-251. [24] SCHMITT J M, XIANG S H, YUNG K M. Speckle in optical coherence tomography[J]. Journal of Biomedical Optics, 1999, 4(1):95-105. doi: 10.1117/1.429925 [25] 高用贺, 李跃杰, 王立伟, 等.光学相干层析成像的视网膜层状结构自动分割[J].中国医疗器械杂志, 2014, 38(2):94-97, 101. doi: 10.3969/j.issn.1671-7104.2014.02.004GAO Y H, LI Y J, WANG L W, et al.. Automated segmentation of retina layer structures on optical coherence tomography[J]. Chinese Journal of Medical Instrumentation, 2014, 38(2):94-97, 101.(in Chinese) doi: 10.3969/j.issn.1671-7104.2014.02.004 [26] ISHIKAWA H, STEIN D M, WOLLSTEIN G, et al.. Macular segmentation with optical coherence tomography[J]. Investigative Ophthalmology and Visual Science, 2005, 46(6):2012-2017. doi: 10.1167/iovs.04-0335 [27] GILBOA G, SOCHEN N, ZEEVI Y Y. Image enhancement and denoising by complex diffusion processes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(8):1020-1036. doi: 10.1109/TPAMI.2004.47 [28] 王健博, 杨航, 吴笑天.结合图像分割的改进导引滤波[J].液晶与显示, 2017, 32(5):380-386. http://d.old.wanfangdata.com.cn/Periodical/yjyxs201705009WANG J B, YANG H, WU X T. Segmentation based improved guided filter[J]. Chinese Journal of Liquid Crystals and Displays, 2017, 32(5):380-386.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/yjyxs201705009 [29] CHITCHIAN S, FIDDY M A, FRIED N M. Denoising during optical coherence tomography of the prostate nerves via wavelet shrinkage using dual-tree complex wavelet transform[J]. Journal of Biomedical Optics, 2009, 14(1):014031. doi: 10.1117/1.3081543 [30] 舒鹏, 孙延奎, 田小林.采用双树复小波和混合概率模型的光学相干层析图像去噪[J].应用科学学报, 2011, 29(5):467-472. doi: 10.3969/j.issn.0255-8297.2011.05.005SHU P, SUN, Y K, TIAN X L. Denoising of optical coherence tomography image using dual-tree complex wavelet transform and mixed probability model[J]. Journal of Applied Sciences, 29(5):467-472.(in Chinese) doi: 10.3969/j.issn.0255-8297.2011.05.005 [31] YUNG K M, LEE S L, SCHMITT J M. Phase-domain processing of optical coherence tomography images[J]. Journal of Biomedical Optics, 1999, 4(1):125-136. doi: 10.1117/1.429942 [32] PIRCHER M, GOTZINGER E, LEITGEB R, et al.. Speckle reduction in optical coherence tomography by frequency compounding[J]. Journal of Biomedical Optics, 2003, 8(3):565-569. doi: 10.1117/1.1578087 [33] PIRCHER M, GOTZINGER E, LEITGEB R, et al.. Measurement and imaging of water concentration in human cornea with differential absorption optical coherence tomography[J]. Optics Express, 2003, 11(18):2190-2197. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=Open J-Gate000001472050 [34] LIN L F, JU Y. Automatic extraction of the anterior chamber contour in OCT images[C]. Proceedings of the 2nd International Symposium on Information Science and Engineering, IEEE, 2009. [35] EICHEL J A, MISHRA A K, FIEGUTH P, et al.. A novel algorithm for extraction of the layers of the cornea[C]. Proceedings of the 2009 Canadian Conference on Computer and Robot Vision, IEEE, 2009: 313-320. [36] LAROCCA F, CHIU S J, MCNABB R P, et al.. Robust automatic segmentation of corneal layer boundaries in SDOCT images using graph theory and dynamic programming[J]. Biomedical Optics Express, 2011, 2(6):1524-1538. doi: 10.1364/BOE.2.001524 [37] 贺琪欲, 李中梁, 王向朝, 等.基于光学相干层析成像的视网膜图像自动分层方法[J].光学学报, 2016, 36(10):1011003. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=gxxb201610009HE Q Y, LI ZH L, WANG X CH, et al.. Automated retinal layer segmentation based on optical coherence tomographic images[J]. Acta Optical Sinica, 2016, 36(10):1011003.(in Chinese) http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=gxxb201610009 [38] KOOZEKANANI D, BOYER K L, ROBERTS C. Tracking the optic nervehead in OCT video using dual eigenspaces and an adaptive vascular distribution model[J]. IEEE Transactions on Medical Imaging, 2003, 22(12):1519-1536. doi: 10.1109/TMI.2003.817753 [39] FERNÁNDEZ D C, SALINAS H M, PULIAFITO C A. Automated detection of retinal layer structures on optical coherence tomography images[J]. Optics Express, 2005, 13(25):10200-10216. doi: 10.1364/OPEX.13.010200 [40] KASS M, WITKIN A, TERZOPOULOS D. Snakes:active contour models[J]. International Journal of Computer Vision, 1988, 1(4):321-331. doi: 10.1007/BF00133570 [41] MUJAT M, CHAN R C, CENSE B, et al.. Retinal nerve fiber layer thickness map determined from optical coherence tomography images[J]. Optics Express, 2005, 13(23):9480-9491. doi: 10.1364/OPEX.13.009480 [42] MISHRA A, WONG A, BIZHEVA K, et al.. Intra-retinal layer segmentation in optical coherence tomography images[J]. Optics Express, 2009, 17(26):23719-23728. doi: 10.1364/OE.17.023719 [43] GHORBEL I, ROSSANT F, BLOCH I, et al.. Automated segmentation of macular layers in OCT images and quantitative evaluation of performances[J]. Pattern Recognition, 2011, 44(8):1590-1603. doi: 10.1016/j.patcog.2011.01.012 [44] GARVIN M K, ABRÁMOFF M D, WU X D, et al.. Automated 3-D intraretinal layer segmentation of macular spectral-domain optical coherence tomography images[J]. IEEE Transactions on Medical Imaging, 2009, 28(9):1436-1447. doi: 10.1109/TMI.2009.2016958 [45] YANG Q, REISMAN C A, WANG ZH G, et al.. Automated layer segmentation of macular OCT images using dual-scale gradient information[J]. Optics Express, 2010, 18(20):21293-21307. doi: 10.1364/OE.18.021293 [46] DUAN J M, TENCH C, GOTTLOB I, et al.. Automated segmentation of retinal layers from optical coherence tomography images using geodesic distance[J]. Pattern Recognition, 2017, 72:158-175. doi: 10.1016/j.patcog.2017.07.004 [47] FULLER A R, ZAWADZKI R J, CHOI S, et al.. Segmentation of three-dimensional retinal image data[J]. IEEE Transactions on Visualization and Computer Graphics, 2007, 13(6):1719-1726. doi: 10.1109/TVCG.2007.70590 [48] SZKULMOWSKI M, WOJTKOWSKI M, SIKORSKI B, et al.. Analysis of posterior retinal layers in spectral optical coherence tomography images of the normal retina and retinal pathologies[J]. Journal of Biomedical Optics, 2007, 12(4):041207. doi: 10.1117/1.2771569 [49] LANG A, CARASS A, HAUSER M, et al.. Retinal layer segmentation of macular OCT images using boundary classification[J]. Biomedical Optics Express, 2013, 4(7):1133-1152. doi: 10.1364/BOE.4.001133 [50] YU K, SHI F, GAO E T, et al.. Shared-hole graph search with adaptive constraints for 3D optic nerve head optical coherence tomography image segmentation[J]. Biomedical Optics Express, 2018, 9(3):962-983. doi: 10.1364/BOE.9.000962 [51] SYC S B, WARNER C V, SAIDHA S, et al.. Cup to disc ratio by optical coherence tomography is abnormal in multiple sclerosis[J]. Journal of the Neurological Sciences, 2011, 302(1-2):19-24. doi: 10.1016/j.jns.2010.12.011 [52] 肖志涛, 娄世良, 吴骏, 等.立体成像眼底相机光学系统设计[J].光学 精密工程, 2018, 26(5):1054-1060. http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201805006XIAO ZH T, LOU SH L, WU J, et al.. Design of optical system for stereo imaging fundus camera[J]. Opt. Precision Eng., 2018, 26(5):1054-1060.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201805006 -
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