Abstract
PurposeTo develop a fully automated algorithm for accurate detection of fovea location in atrophic age-related macular degeneration (AMD), based on spectral-domain optical coherence tomography (SD-OCT) scans.MethodsImage processing was conducted on a cohort of patients affected by geographic atrophy (GA). SD-OCT images (cube volume) from 55 eyes (51 patients) were extracted and processed with a layer segmentation algorithm to segment Ganglion Cell Layer (GCL) and Inner Plexiform Layer (IPL). Their en face thickness projection was convolved with a 2D Gaussian filter to find the global maximum, which corresponded to the detected fovea. The detection accuracy was evaluated by computing the distance between manual annotation and predicted location.ResultsThe mean total location error was 0.101±0.145mm; the mean error in horizontal and vertical en face axes was 0.064±0.140mm and 0.063±0.060mm, respectively. The mean error for foveal and extrafoveal retinal pigment epithelium and outer retinal atrophy (RORA) was 0.096±0.070mm and 0.107±0.212mm, respectively. Our method obtained a significantly smaller error than the fovea localization algorithm inbuilt in the OCT device (0.313±0.283mm, p <.001) or a method based on the thinnest central retinal thickness (0.843±1.221, p <.001). Significant outliers are depicted with the reliability score of the method.ConclusionDespite retinal anatomical alterations related to GA, the presented algorithm was able to detect the foveal location on SD-OCT cubes with high reliability. Such an algorithm could be useful for studying structural-functional correlations in atrophic AMD and could have further applications in different retinal pathologies.
Highlights
The fovea is the region of the retina with the highest density of cone photoreceptors, and it is responsible for sharp central vision [1]
We propose an automated algorithm to detect foveal location based on the detection of inner retinal layers in atrophic age-related macular degeneration (AMD) eyes
We hereby propose an automated algorithm to detect foveal location based on spectral-domain optical coherence tomography (SD-OCT) volume scans and we report its performance in geographic atrophy (GA) patients
Summary
The fovea is the region of the retina with the highest density of cone photoreceptors, and it is responsible for sharp central vision [1]. On optical coherence tomography of healthy eyes, the fovea is identifiable within the central macular region owing to its depression. The recognition of retinal landmarks on OCT could be challenging in several retinal pathologies, either for anatomical alterations of the retinal architecture or for image artifacts [4, 5]. One such disease is age-related macular degeneration (AMD) with geographic atrophy (GA), characterized by atrophy of outer retinal tissue, retinal pigment epithelium and choriocapillaris [6, 7]. Their distance to the fovea is of particular interest, as the visual impact largely depends on the fovea-related location of the atrophy [8, 9]
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