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Proceedings Paper

Optimized retinal nerve fiber layer segmentation based on optical reflectivity and birefringence for polarization-sensitive optical coherence tomography
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Paper Abstract

Segmentation of the retinal nerve fiber layer (RNFL) from swept source polarization-sensitive optical coherence tomography (SS-PSOCT) images is required to determine RNFL thickness and calculate birefringence. Traditional RNFL segmentation methods based on image processing and boundary detection algorithms utilize only optical reflectivity contrast information, which is strongly affected by speckle noise. We present a novel approach to segment the retinal nerve fiber layer (RNFL) using SS-PSOCT images including both optical reflectivity and phase retardation information. The RNFL anterior boundary is detected based on optical reflectivity change due to refractive index difference between the vitreous and inner limiting membrane. The posterior boundary of the RNFL is a transition zone composed of birefringent axons extending from retinal ganglion cells and may be detected by a change in birefringence. A posterior boundary detection method is presented that segments the RNFL by minimizing the uncertainty of RNFL birefringence determined by a Levenberg-Marquardt nonlinear fitting algorithm. Clinical results from a healthy volunteer show that the proposed segmentation method estimates RNFL birefringence and phase retardation with lower uncertainty and higher continuity than traditional intensity-based approaches.

Paper Details

Date Published: 24 September 2011
PDF: 10 pages
Proc. SPIE 8135, Applications of Digital Image Processing XXXIV, 81351R (24 September 2011); doi: 10.1117/12.892826
Show Author Affiliations
Bingqing Wang, The Univ. of Texas at Austin (United States)
Amit S. Paranjape, The Univ. of Texas at Austin (United States)
Biwei Yin, The Univ. of Texas at Austin (United States)
Shuang Liu, The Univ. of Texas at Austin (United States)
Mia K. Markey, The Univ. of Texas at Austin (United States)
Thomas E. Milner, The Univ. of Texas at Austin (United States)
H. Grady Rylander, The Univ. of Texas at Austin (United States)


Published in SPIE Proceedings Vol. 8135:
Applications of Digital Image Processing XXXIV
Andrew G. Tescher, Editor(s)

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