Robust segmentation of intraretinal layers in the normal human fovea using a novel statistical model based on texture and shape analysis

doi:10.1364/OE.18.014730

Robust segmentation of intraretinal layers in the normal human fovea using a novel statistical model based on texture and shape analysis

Vedran Kajić, Boris Považay, Boris Hermann, Bernd Hofer, David Marshall, Paul L. Rosin, and Wolfgang Drexler »View Author Affiliations

Optics Express, Vol. 18, Issue 14, pp. 14730-14744 (2010)
http://dx.doi.org/10.1364/OE.18.014730

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Abstract

A novel statistical model based on texture and shape for fully automatic intraretinal layer segmentation of normal retinal tomograms obtained by a commercial 800nm optical coherence tomography (OCT) system is developed. While existing algorithms often fail dramatically due to strong speckle noise, non-optimal imaging conditions, shadows and other artefacts, the novel algorithm’s accuracy only slowly deteriorates when progressively increasing segmentation task difficulty. Evaluation against a large set of manual segmentations shows unprecedented robustness, even in the presence of additional strong speckle noise, with dynamic range tested down to 12dB, enabling segmentation of almost all intraretinal layers in cases previously inaccessible to the existing algorithms. For the first time, an error measure is computed from a large, representative manually segmented data set (466 B-scans from 17 eyes, segmented twice by different operators) and compared to the automatic segmentation with a difference of only 2.6% against the inter-observer variability.

OCIS Codes
(100.0100) Image processing : Image processing
(170.4500) Medical optics and biotechnology : Optical coherence tomography
(170.4580) Medical optics and biotechnology : Optical diagnostics for medicine
(100.3008) Image processing : Image recognition, algorithms and filters

ToC Category:
Medical Optics and Biotechnology

History
Original Manuscript: May 14, 2010
Revised Manuscript: June 20, 2010
Manuscript Accepted: June 21, 2010
Published: June 24, 2010

Virtual Issues
Vol. 5, Iss. 11 Virtual Journal for Biomedical Optics

Citation
Vedran Kajić, Boris Považay, Boris Hermann, Bernd Hofer, David Marshall, Paul L. Rosin, and Wolfgang Drexler, "Robust segmentation of intraretinal layers in the normal human fovea using a novel statistical model based on texture and shape analysis," Opt. Express 18, 14730-14744 (2010)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=oe-18-14-14730

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References

W. Drexler, and J. G. Fujimoto, Optical Coherence Tomography: Technology and Applications (Springer, 2008).
T. Fabritius, S. Makita, M. Miura, R. Myllylä, and Y. Yasuno, “Automated segmentation of the macula by optical coherence tomography,” Opt. Express 17(18), 15659–15669 (2009). [CrossRef] [PubMed]
R. J. Zawadzki, S. S. Choi, S. M. Jones, S. S. Oliver, and J. S. Werner, “Adaptive optics-optical coherence tomography: optimizing visualization of microscopic retinal structures in three dimensions,” J. Opt. Soc. Am. A 24(5), 1373 (2007). [CrossRef]
M. M. K. Garvin, M. M. D. Abramoff, R. R. Kardon, S. S. R. Russell, X. X. Wu, and M. M. Sonka, “Intraretinal Layer Segmentation of Macular Optical Coherence Tomography Images Using Optimal 3-D Graph Search,” IEEE Trans. Med. Imaging 27(10), 1495–1505 (2008). [CrossRef] [PubMed]
D. Cabrera Fernández, H. M. Salinas, and C. A. Puliafito, “Automated detection of retinal layer structures on optical coherence tomography images,” Opt. Express 13(25), 10200–10216 (2005). [CrossRef] [PubMed]
M. Mujat, R. Chan, B. Cense, B. Park, C. Joo, T. Akkin, T. Chen, and J. de Boer, “Retinal nerve fiber layer thickness map determined from optical coherence tomography images,” Opt. Express 13(23), 9480–9491 (2005). [CrossRef] [PubMed]
D. Koozekanani, K. Boyer, and C. Roberts, “Retinal thickness measurements from optical coherence tomography using a Markov boundary model,” IEEE Trans. Med. Imaging 20(9), 900–916 (2001). [CrossRef] [PubMed]
D. Tolliver, Y. Koutis, H. Ishikawa, J. S. Schuman, and G. L. Miller, “Unassisted Segmentation of Multiple Retinal Layers via Spectral Rounding,” in ARVO(2008).
A. Mishra, A. Wong, K. Bizheva, and D. A. Clausi, “Intra-retinal layer segmentation in optical coherence tomography images,” Opt. Express 17(26), 23719–23728 (2009). [CrossRef]
I. W. Selesnick, R. G. Baraniuk, and N. G. Kingsbury, “The Dual-Tree Complex Wavelet Transform,” IEEE Signal Process. Mag. 22(6), 123–151 (2005). [CrossRef]
A. Mishra, A. Wong, D. A. Clausi, and P. W. Fieguth, “Quasi-random nonlinear scale space,” Pattern Recognit. Lett. In Press. (Corrected Proof).
A. Wong, A. Mishra, K. Bizheva, and D. A. Clausi, “General Bayesian estimation for speckle noise reduction in optical coherence tomography retinal imagery,” Opt. Express 18(8), 8338–8352 (2010). [CrossRef] [PubMed]
P. Thevenaz, and M. Unser, “A pyramid approach to sub-pixel image fusion based on mutual information,” in Image Processing, 1996. Proceedings., International Conference on(1996), p. 265.
C. O. S. Sorzano, P. Thevenaz, and M. Unser, “Elastic registration of biological images using vector-spline regularization,” BIEEE Biomed. Eng. 52(4), 652–663 (2005). [CrossRef]
A. K. Mishra, P. W. Fieguth, and D. A. Clausi, “Decoupled Active Contour (DAC) for Boundary Detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence 99.
T. F. Cootes, G. J. Edwards, and C. J. Taylor, “Active Appearance Models,” IEEE Trans. Pattern Anal. Mach. Intell. 23(6), 681–685 (2001). [CrossRef]
M. Scholz, M. Fraunholz, and J. Selbig, “Nonlinear Principal Component Analysis: Neural Network Models and Applications,” in Principal Manifolds for Data Visualization and Dimension Reduction(2007), pp. 44–67.
M. Scholz, F. Kaplan, C. L. Guy, J. Kopka, and J. Selbig, “Non-linear PCA: a missing data approach,” Bioinformatics 21(20), 3887–3895 (2005). [CrossRef] [PubMed]
A. A. Efros, and W. T. Freeman, “Image quilting for texture synthesis and transfer,” in Proceedings of the 28th annual conference on Computer graphics and interactive techniques(ACM, 2001), pp. 341–346.

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