Article

Automated extraction and quantification of macular drusen from fundal photographs

Princess Margaret Hospital, Perth
Australian and New Zealand Journal of Ophthalmology 11/1994; 22(1):7 - 12. DOI: 10.1111/j.1442-9071.1994.tb01688.x

ABSTRACT 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).

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    • "Several studies on automatic detection of drusen have been published in the last twentyyears . The majority of works were based on applying image thresholds to separate drusen from background or other structures [2] [3] [4] [5] [6] [7] [8] [9]. We have also contributed to this subject by introducing new image processing algorithms for illumination correction [10] and for drusen detection and modeling [11] [12]. "
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    • "Uneven illumination artifacts of the retina forced the application of sophisticated adaptive thesholding utilizing Otsu's method, e.g. Morgan et al. and others [5]. Interactive techniques have been applied, driven by limitations of automated segmentation and algorithms. "
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    • "Both algorithms achieved similar results on images from the same patient but they produced a considerable number of false positive detections. In 1994 Morgan et al. [6] from University of Western Australia published a paper where it was proposed an automatic Drusen quantification based on the application of the Otsu threshold to local windows of 16x16 pixels. The results obtained with the automatic quantification were compared with manual counting done by three experts. "
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