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access icon free Automated method for the detection and segmentation of drusen in colour fundus image for the diagnosis of age-related macular degeneration

© The Institution of Engineering and Technology
Received 04/07/2017, Accepted 02/01/2018, Revised 20/12/2017, Published 05/01/2018

Age-related macular degeneration (AMD) is one of the main reasons for visual impairment worldwide. The assessment of risk for the development of AMD requires reliable detection and quantitative mapping of retinal abnormalities that are considered as precursors of the disease. Typical signs of the latter are the so-called drusen that appear as yellowish spots in the retina. Automated detection and segmentation of drusen provide vital information about the severity of the disease. The authors propose a novel method for the detection and segmentation of drusen in colour fundus images. The method combines colour information of the object with its boundary information for the accurate detection and segmentation of drusen. To perform non-uniform illumination correction and to minimise inter-subject variability a novel colour normalisation method has been proposed. Experiments are conducted on publicly available STARE and ARIA datasets. The method achieves an overall accuracy of 96.62% which is about 4% higher than the state-of-the-art method. The sensitivity and specificity of the proposed method are 95.96 and 97.64%, respectively.

Inspec keywords: image colour analysis; object detection; medical image processing; image segmentation; eye

Other keywords: STARE dataset; retina; drusen segmentation; inter-subject variability minimization; disease; automated method; quantitative mapping; nonuniform illumination correction; ARIA datasets; drusen detection; AMD; colour fundus image; colour normalisation method; age-related macular degeneration diagnosis; retinal abnormalities detection

Subjects: Computer vision and image processing techniques; Optical, image and video signal processing; Biomedical measurement and imaging; Medical and biomedical uses of fields, radiations, and radioactivity; health physics; Biology and medical computing; Patient diagnostic methods and instrumentation

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