Exact Surface Registration of Retinal Surfaces From 3-D Optical Coherence Tomography Images

Abstract

Nonrigid registration of optical coherence tomography (OCT) images is an important problem in studying eye diseases, evaluating the effect of pharmaceuticals in treating vision loss, and performing group-wise cross-sectional analysis. High dimensional nonrigid registration algorithms required for cross-sectional and longitudinal analysis are still being developed for accurate registration of OCT image volumes, with the speckle noise in images presenting a challenge for registration. Development of algorithms for segmentation of OCT images to generate surface models of retinal layers has advanced considerably and several algorithms are now available that can segment retinal OCT images into constituent retinal surfaces. Important morphometric measurements can be extracted if accurate surface registration algorithm for registering retinal surfaces onto corresponding template surfaces were available. In this paper, we present a novel method to perform multiple and simultaneous retinal surface registration, targeted to registering surfaces extracted from ocular volumetric OCT images. This enables a point-to-point correspondence (homology) between template and subject surfaces, allowing for a direct, vertex-wise comparison of morphometric measurements across subject groups. We demonstrate that this approach can be used to localize and analyze regional changes in choroidal and nerve fiber layer thickness among healthy and glaucomatous subjects, allowing for cross-sectional population wise analysis. We also demonstrate the method's ability to track longitudinal changes in optic nerve head morphometry, allowing for within-individual tracking of morphometric changes. This method can also, in the future, be used as a precursor to 3-D OCT image registration to better initialize nonrigid image registration algorithms closer to the desired solution.

Quantifying Variability in Longitudinal Peripapillary RNFL and Choroidal Layer Thickness Using Surface Based Registration of OCT Images

“…13,14 Twelve normal eyes of six subjects were imaged nine times over 3 weeks, and BMO dimensions, RNFL thickness, and choroidal thickness were measured. It should be noted that the subjects used in this analysis are all young and healthy.…”

“…These were corrected by manually specifying registration landmarks. The nonrigid registration method was validated in our previous work 14 using clinical optic nerve head OCT images and artificial phantom data, which showed errors less than the coherence length at all vertices.…”

“…14 First, the surfaces were represented by currents of geometric measure theory, which allows one to measure the closeness of two surfaces via a norm in a Hilbert space. 19 The optimal transformation of the target (follow-up) to the template (baseline) was then found as a smooth diffeomorphism, bringing the two surfaces into close proximity.…”

“…13,14 In Gibson et al, 13 intensity-based 3D rigid and nonrigid registrations were performed on optic cup surfaces followed by spherical mapping and spherical demons algorithm. Lee et al 14 extended upon this method by introducing current-based nonrigid registration of the surfaces prior to the demons registration. Our approach presents a generalized and versatile framework that can be used to track arbitrary measurements on retinal surfaces in high spatial resolution.…”

“…14 Starting with the working hypothesis that there is no variability in measurements such as RNFL/choroidal thickness made from longitudinal repeated scans, we demonstrate experiments to assess this normal-range short-term variability of the registration-based peripapillary measurements. The experiments were designed to focus on healthy subjects imaged repeatedly over a short span of 3 weeks to limit the observed changes to normative noise, excluding substantial and significant changes that may occur over a longer period of time.…”