Validated Filter-Based Photoreceptor Count Algorithm on Retinal Heidelberg High Magnification Module™ Images in Healthy and Pathological Conditions

Abstract

Recently introduced, the Heidelberg Engineering™ high magnification module enables in vivo visualization of cone photoreceptor cells. Currently, a reliable analysis of cone mosaic on high magnification module images is hindered by an unfavorable signal-to-noise ratio. In this paper, we describe how a novel high magnification module high-pass filter may enhance cone signals in healthy participants and patients. We compared the cone counts of our filter-based algorithm to the counts of two human graders. We found a good to excellent intragrader and intergrader correlation in both patients and healthy participants. We identified a good correlation between the average cone counts of both graders and high-pass filter cone counts in patients and healthy participants. We observed no significant difference between manual and filter-based counts via the Bland–Altman analysis. In conclusion, a quantitative cone analysis on high magnification module images is feasible manually by human graders and automatically by a filter-based algorithm. However, larger datasets are needed to improve repeatability and consistency by training human graders.