Detection of hard exudates using 2D Otsu algorithm in digital retinal fundus image

Kayal, Diptoneel; Banerjee, Sreeparna

doi:10.1007/s40012-016-0138-4

Cited by 5 publications

(1 citation statement)

References 17 publications

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“…Therefore, this similarity leads to increase false positive shapes when detecting the HEs. Accordingly, it is essential to remove OD, as done in several HE detection methods [12,16,9,5,11]. The method proposed in [23] insures locating the OD based on circularity and intensity through applying the radon transform.…”

Section: Optic Disk Locationmentioning

confidence: 99%

Fast and accurate mobile-aided screening system of moderate diabetic retinopathy

Elloumi

Mbarek

Boukadida

et al. 2021

Thirteenth International Conference on Machine Vision

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The Diabetic Retinopathy (DR) is a worldwide eye disease that causes visual damages and can leads to blindness. Therefore, the detection of the DR in the early stages is highly recommended. However, a delay is registered for ensuring early DR diagnosis which caused by the low-rate of the ophthalmologists, the deficiency of diagnosis equipment and the lack of mobility of elderly patients.In this paper, the main objective is to provide a mobile-aided screening system of moderate DR. Within this aim, we propose a classifier-based method which is based on detecting the Hard Exudate (HE) lesions that occur in moderate DR stage. A set of features are extracted to ensure an accurate and robust detection with respect to modest quality of fundus images. Moreover, the detection is provided in a low complexity processing to be suitable for mobile device. The aimed system corresponds to the implementation of the method on a smartphone associated to an optical lens for capturing fundus image. The system reached satisfactory screening performance where an accuracy of 98.36%, a sensitivity of 100% and specificity of 96.45% are registered using the DIARETDB1 fundus image databases. Moreover, the screening is performed in an average execution time of 2.68 seconds.

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