Automated extraction and quantification of macular drusen from fundal photographs
The objective quantification of drusen (and other macular lesions) should have applications epidemi-ologically, in the study of the natural history of drusen, and with such instruments as the scanning laser ophthalmoscope. The automated extraction of drusen from photographs is technically difficult because of uneven macular reflectance, and the confusing pattern of darker vessels. We have developed a method using an IBM personal computer, an image digitising board and specially written software. Once the image is digitised, no further input from the operator is necessary. We present the results of manual counting versus automated counting on a small series of patients with drusen. The automated technique is highly reproducible, and will calculate the retinal area occupied by drusen. The area and numbers of drusen can be compared over time, giving an index of progression. Hard drusen are fairly well detected, but the detection of soft drusen with their lower contrast remains a problem. The technique cannot distinguish between drusen and other pale lesions (e.g., atrophic retinal changes).
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.