RESUMEN
We present a fully automatic montage pipeline for adaptive optics SLO retinal images. It contains a flexible module to estimate the translation between pairwise images. The user can change modules to accommodate the alignment of the dataset using the most appropriate alignment technique, provided that it estimates the translation between image pairs and provides a quantitative confidence metric for the match between 0 and 1. We use these pairwise comparisons and associated metrics to construct a graph where nodes represent frames and edges represent the overlap relations. We use a small diameter spanning tree to determine the best pairwise alignment for each image based on the entire set of image relations. The final stage of the pipeline is a blending module that uses dynamic programming to improve the smoothness of the transition between frames. Data sets ranging from 26 to 119 images were obtained from individuals aged 24 to 81 years with a mix of visually normal control eyes and eyes with glaucoma or diabetes. The resulting automatically generated montages were qualitatively and quantitatively compared to results from semi-automated alignment. Data sets were specifically chosen to include both high quality and medium quality data. The results obtained from the automatic method are comparable or better than results obtained by an experienced operator performing semi-automated montaging. For the plug-in pairwise alignment module, we tested a technique that utilizes SIFT + RANSAC, Normalized cross-correlation (NCC) and a combination of the two. This pipeline produces consistent results not only on outer retinal layers, but also on inner retinal layers such as a nerve fiber layer or images of the vascular complexes, even when images are not of excellent quality.
RESUMEN
Purpose: Cones in diabetic patients are at risk due to metabolic and vascular changes. By imaging retinal vessel modeling at high magnification, we reduced its impact on cone distribution measurements. The retinal vessel images and retinal thickness measurements provided information about cone microenvironment. Methods: We compared cone data in 10 diabetic subjects (28-78 yr) to our published norms from 36 younger and 10 older controls. All subjects were consented and tested in a manner approved by the Indiana University Institutional Review Board, which adhered to the Declaration of Helsinki. Custom adaptive optics scanning laser ophthalmoscopy (AOSLO) was used to image cones and retinal microcirculation. We counted cones in a montage of foveal and temporal retina, using four non-contiguous samples within 0.9-7 deg that were selected for best visibility of cones and least pathology. The data were fit with a two parameter exponential model: ln(cone density) = a * microns eccentricity + b. These results were compared to retinal thickness measurements from SDOCT. Results: Diabetic cone maps were more variable than in controls and included patches, or unusually bright and dark cones, centrally and more peripherally. Model parameters and total cones within the central 14 deg of the macula differed across diabetic patients. Total cones fell into two groups: similar to normal for 5 vs. less than normal for 2 of 2 younger diabetic subjects and 3 older subjects, low but not outside the confidence limits. Diabetic subjects had all retinal vascular remodeling to varying degrees: microaneurysms; capillary thickening, thinning, or bends; and vessel elongation including capillary loops, tangles, and collaterals. Yet SD-OCT showed that no diabetic subject had a Total Retinal Thickness in any quadrant that fell outside the confidence limits for controls. Conclusions: AOSLO images pinpointed widespread retinal vascular remodeling in all diabetic eyes, but the SDOCT showed no increased retinal thickness. Cone reflectivity changes were found in all diabetic patients, but significantly low cone density in only some. These results are consistent with early changes to neural, glial, or vascular components of the retinal without significant retinal thickening due to exudation.