Automatic Anisotropic Diffusion Filtering and Graph-search Segmentation of Macular Spectral-domain Optical Coherence Tomographic (SD-OCT) Images

A.      Usha; Nijisha      Shajil; M.      Sasikala

doi:10.2174/1573405613666171201155119

Abstract

Background: Optical Coherence Tomography (OCT) is a non-invasive medical imaging technique that provides high-resolution cross-sectional images of the retina. There is a need to develop algorithms for obtaining quantitative and qualitative information about the retina which are essential for assessing and managing eye conditions.

Methods: This work emphasizes on an automated image processing algorithm for segmenting retinal layers. It involves preprocessing of the acquired retinal SD-OCT image (B-scan) using the proposed automatic Anisotropic diffusion filter, followed with contrast stretching to suppress intrinsic speckle noise without blurring structural edges. Graph search segmentation using Dijkstra algorithm with a combination of threshold and axial gradient as the cost function is used to segment the retinal layer boundaries.

Results: The algorithm was performed and the average thickness of the segmented retina was computed for the 3D retinal scan (128 B-scans) of 8 subjects (4 normal and 4 abnormal) using Early Treatment Diabetic Retinopathy Screening (ETDRS) chart.

Conclusion: Segmentation was evaluated using manually segmented B-scan by an Ophthalmologist as ground truth and accuracy was found to be 99.14 ± 0.27%.

Keywords: Speckle, anisotropic diffusion, graph search segmentation, ETDRS, SD-OCT, retina.

Graphical Abstract

[1] 
Image Source: Gray scale image OCT scan of retina. Available
from: https://www.luxotticalearning.co.nz/oct-analysis-part-1-l6024 /
[2] 
Kafieh R, Rabbani H, Kermani S. A review of algorithms for segmentation of optical coherence tomography from retina. Med Sign Sens  2013; 3(1): 45-60.
[3] 
Tian J, Varga B, Tatrai E, et al. Performance evaluation of automated segmentation software on optical coherence tomography volume data. Biophotonics  2016; 9(5): 478-89.
[4] 
Abràmoff MD, Garvin MK, Sonka M. Retinal imaging and image analysis. IEEE Rev Biomed Eng  2010; 3: 169-208.
[5] 
Wu M, Leng T, de Sisternes L, Rubin DL, Chen Q. Automated segmentation of optic disc in SDOCT images and cup-to-disc ratios quantification by patch searching-based neural canal opening detection. OSA Opt Express  2015; 23(24): 31216-29.
[6] 
Tsiotsios C, Petrou M. On the choice of the parameters for anisotropic diffusion in image processing. Patt Recogn  2013; 46: 1369-81.
[7] 
Gao E, Shi F, Zhu W, Chen B, Chen H, Chen X. Comparison of retinal thickness measurements of normal eyes between topcon algorithm and a graph-based algorithm. PLoS One  2014; 81-8.
[8] 
Szkulmowski M, Gorczynska I, Szlag D, Sylwestrzak M, Kowalczyk A, Wojtkowski M. Efficient reduction of speckle noise in Optical Coherence Tomography. OSA Opt Express  2012; 20(2): 1337-59.
[9] 
Schmitt JM, Xiang SH, Yung KM. Speckle in optical coherence tomography: An overview. Biomed Opt  1999; 4(1): 146: 95-105.
[10] 
Perona P, Malik J. Scale-space and edge detection using anisotropic diffusion. Patt Anal Mach Intel  1990; 12(7): 629-39.
[11] 
Yu Jin Zhang. A review of recent evaluation methods for image segmentation. IEEE Sig Process Applic  2001; 1: 148-51.
[12] 
Mrazek P, Navara M. Selection of optimal stopping time for nonlinear diffusion filtering. Comp Vis  2003; 52(2): 189-203.
[13] 
Jain AK. Fundamentals of digital image processing. Pearson Education 2003.
[14] 
Ehnes A, Wenner Y, Friedburg C, et al. Optical Coherence Tomography (OCT) device independent intraretinal layer segmentation. Transl Vis Sci Technol  2014; 3(1): 1-16.
[15] 
Garvin MK, Abràmoff MD, Kardon R, Russell SR, Wu X, Sonka M. Intraretinal Layer Segmentation of Macular Optical Coherence Tomography Images Using Optimal 3-D Graph Search. IEEE Trans Med Imaging  2008; 27(10): 1495-505.
[16] 
Bagci AM, Shahidi M, Ansari R, Blair M, Blair NP, Zelkha R. Thickness profiles of retinal layers by optical coherence tomography image segmentation. Am J Ophthalmol  2008; 146(5): 679-87.
[17] 
Wood A, Binns A, Margrain T, et al. Retinal and choroidal thickness in early agerelated macular degeneration. Am J Ophthalmol  2011; 152(6): 1030-8.
[18] 
Pradhan ZS, Braganza A, Abraham LM. Determinants of macular thickness in normal Indian eyes. Clinic Ophthalmol Res  2013; 1(1): 11-6.
[19] 
Canny J. A computational approach to edge detection. IEEE Patt Anal Mach Intell  1986; 8(6): 679-98.
[20] 
TOPCON 3D OCT series normative database. Available from: www.topconmedical.com

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DOI https://dx.doi.org/10.2174/1573405613666171201155119	Print ISSN 1573-4056
Publisher Name Bentham Science Publisher	Online ISSN 1875-6603

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Automatic Anisotropic Diffusion Filtering and Graph-search Segmentation of Macular Spectral-domain Optical Coherence Tomographic (SD-OCT) Images

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