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

• Published in: IET image processing Vol. 12; no. 6; pp. 919 - 927
• Main Authors: Mohaimin, Sultan Mohammad, Saha, Sajib Kumar, Khan, Alve Mahamud, Mohammad Arif, Abu Shamim, Kanagasingam, Yogesan
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 01.06.2018
• Subjects: age‐related macular degeneration diagnosis; AMD; ARIA datasets; automated method; colour fundus image; colour normalisation method; disease; drusen detection; drusen segmentation; eye; image colour analysis; image segmentation; inter‐subject variability minimization; medical image processing; nonuniform illumination correction; object detection; quantitative mapping; Research Article; retina; retinal abnormalities detection; STARE dataset; drusen detection; automated method; quantitative mapping; disease; object detection; drusen segmentation; age-related macular degeneration diagnosis; colour fundus image; eye; colour normalisation method; STARE dataset; nonuniform illumination correction; image segmentation; retina; ARIA datasets; AMD; retinal abnormalities detection; image colour analysis; medical image processing; inter-subject variability minimization

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 la...