Abstract
The lamina cribrosa is affected by intraocular pressure, which is the major risk of glaucoma. However, the capability to evaluate the lamina cribrosa in vivo has been limited until recently due to poor image quality and the posterior laminar displacement of glaucomatous eyes. In this study, we propose an automatic method to measure the anterior lamina cribrosa surface depth (ALCSD), including a method for detecting Bruch’s membrane opening (BMO) based on k-means and region-based active contour. An anterior lamina cribrosa surface segmentation method based on energy constraint is also proposed. In BMO detection, we initialize the Chan-Vese active contour model by using the segmentation map of the k-means cluster. In the segmentation of anterior lamina cribrosa surface, we utilize the energy function in each A-scan to establish a set of candidates. The points in the set that fail to meet the constraints are removed. Finally, we use the B-spline fitting method to obtain the results. The proposed automatic method can model the posterior laminar displacement by measuring the ALCSD. This method achieves a mean error of 45.34 μm in BMO detection. The mean errors of the anterior lamina cribrosa surface are 94.1% within five pixels and 76.1% within three pixels.
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References
Cook C, Foster P. Epidemiology of glaucoma: What’s new? Canadian Journal of Ophthalmology, 2012, 47(3): 223-226.
Minckler D S, Bunt A H, Johanson G W. Orthograde and retrograde axoplasmic transport during acute ocular hypertension in the monkey. Investigative Ophthalmology & Visual Science, 1977, 16(5): 426-441.
Quigley H A, Addicks E M. Regional differences in the structure of the lamina cribrosa and their relation to glaucomatous optic nerve damage. Archives of Ophthalmology, 1981, 99(1): 137-143.
Yan D B, Coloma F M, Metheetrairut A, Trope G E, Heathcote J G, Ethier C R. Deformation of the lamina cribrosa by elevated intraocular pressure. British Journal of Ophthalmology, 1994, 78(8): 643-648.
Jonas J B, Wang N, Yang D. Translamina cribrosa pressure difference as potential element in the pathogenesis of glaucomatous optic neuropathy. The Asia-Pacific Journal of Ophthalmology, 2016, 5(1): 5-10.
Reis A S C, O’Leary N, Stanfield M J, Shuba L M, Nicolela M T, Chauhan B C. Laminar displacement and prelaminar tissue thickness change after glaucoma surgery imaged with optical coherence tomography. Investigative Ophthalmology & Visual Science, 2012, 53(9): 5819-5826.
Seo J H, Kim T W, Weinreb R N. Lamina cribrosa depth in healthy eyes. Investigative Ophthalmology & Visual Science, 2014, 55(3): 1241-1251.
Spaide R F, Koizumi H, Pozzoni M C. Enhanced depth imaging spectral-domain optical coherence tomography. American Journal of Ophthalmology, 2008, 146(4): 496-500.
Abe R Y, Gracitelli C P B, Diniz-Filho A, Tatham A J, Medeiros F A. Lamina cribrosa in glaucoma: Diagnosis and monitoring. Current Ophthalmology Reports, 2015, 3(2): 74-84.
Furlanetto R L, Park S C, Damle U J, Sieminski S F, Kung Y, Siegal N, Ritch R. Posterior displacement of the lamina cribrosa in glaucoma: In vivo interindividual and intereye comparisons. Investigative Ophthalmology & Visual Science, 2013, 54(7): 4836-4842.
Miri M S, Robles V A, Abrmoff M D, Kwon Y H, Garvin M K. Incorporation of gradient vector flow field in a multimodal graph-theoretic approach for segmenting the internal limiting membrane from glaucomatous optic nerve head-centered SD-OCT volumes. Computerized Medical Imaging and Graphics, 2017, 55: 87-94.
Shah A, Wang J K, Garvin M K, Sonka M, Wu X. Automated surface segmentation of internal limiting membrane in spectral-domain optical coherence tomography volumes with a deep cup using a 3-D range expansion approach. In Proc. the 11th IEEE International Symposium on Biomedical Imaging (ISBI), Apr. 29-May 2, 2014, pp.1405-1408.
Lu S, Cheung C Y L, Liu J, Lim J H, Leung C K S, Wong T Y. Automated layer segmentation of optical coherence tomography images. IEEE Transactions on Biomedical Engineering, 2010, 57(10): 2605-2608.
Belghith A, Bowd C, Medeiros F A, Weinreb R N, Zangwill L M. Automated segmentation of anterior lamina cribrosa surface: How the lamina cribrosa responds to intraocular pressure change in glaucoma eyes? In Proc. the 12th IEEE International Symposium on Biomedical Imaging (ISBI), Apr. 2015, pp.222-225.
Chan T F, Vese L A. Active contours without edges. IEEE Transactions on Image Processing, 2001, 10(2): 266-277.
GirardM J, Strouthidis N G, Ethier C R, Mari J M. Shadow removal and contrast enhancement in optical coherence tomography images of the human optic nerve head. Investigative Ophthalmology & Visual Science, 2011, 52(10): 7738-7748.
Foin N, Mari J M, Davies J E, Di Mario C, Girard M J. Imaging of coronary artery plaques using contrast-enhanced optical coherence tomography. European Heart Journal–Cardiovascular Imaging, 2013, 14(1): 85.
Zhang Q, Wang Y X, Li J J et al. Optical coherence tomography of prelaminar tissue and its relationship with oculopathy. International Review of Ophthalmology, 2017, 41(1): 8-13. (in Chinese)
HussainM A, Bhuiyan A, Ramamohanarao K. Disc segmentation and BMO-MRW measurement from SD-OCT image using graph search and tracing of three bench mark reference layers of retina. In Proc. IEEE International Conference on Image Processing (ICIP), Sept. 2015, pp.4087-4091.
Chang J, Fisher J W. Efficient MCMC sampling with implicit shape representations. In Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 2011, pp.2081-2088.
Ren R, Yang H, Gardiner S K, Fortune B, Hardin C, Demirel S, Burgoyne C F. Anterior lamina cribrosa surface depth, age, and visual field sensitivity in the Portland progression project. Investigative Ophthalmology & Visual Science, 2014, 55(3): 1531-1539.
Cheung C Y, Chen D, Wong T Y et al. Determinants of quantitative optic nerve measurements using spectral domain optical coherence tomography in a population-based sample of non-glaucomatous subjects. Investigative Ophthalmology & Visual Science, 2011, 52(13): 9629-9635.
Patel N B, Lim M, Gajjar A, Evans K B, Harwerth R S. Age-associated changes in the retinal nerve fiber layer and optic nerve head. Investigative Ophthalmology & Visual Science, 2014, 55(8): 5134-5143.
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Chen, ZL., Peng, P., Zou, BJ. et al. Automatic Anterior Lamina Cribrosa Surface Depth Measurement Based on Active Contour and Energy Constraint. J. Comput. Sci. Technol. 32, 1214–1221 (2017). https://doi.org/10.1007/s11390-017-1795-y
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DOI: https://doi.org/10.1007/s11390-017-1795-y