Optimized retinal nerve fiber layer segmentation based on optical reflectivity and birefringence for polarization-sensitive optical coherence tomography
2011
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.
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