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Combining algorithms for automatic detection of optic disc and macula in fundus images
Authors:Rashid Jalal Qureshi  Laszlo Kovacs  Balazs Harangi  Brigitta Nagy  Tunde Peto  Andras Hajdu
Affiliation:1. Faculty of Informatics, University of Debrecen, POB 12, 4010 Debrecen, Hungary;2. NIHR Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, 162 City Road, London EC1V 2PD, UK;1. Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan;2. Division of Endocrinology and Metabolism, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan;3. Department of Medical Imaging, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan;1. Campus Tecnológico de Alegrete, Universidade Federal do Pampa, Av. Tiarajú 810, Alegrete, RS, CEP 97546-550, Brazil;2. Instituto de Informática, Universidade Federal do Rio Grande do Sul, Av. Bento Gonçalves 9500, Porto Alegre, RS, CEP 91509-900, Brazil;3. Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Rua Ramiro Barcelos 2400, Porto Alegre, RS, CEP 90035-003, Brazil;1. INEB - Instituto de Engenharia Biomédica, Universidade do Porto, Porto, Portugal;2. Faculdade de Engenharia, Universidade do Porto, Campus da FEUP, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal;3. INESC TEC - INESC Technology and Science, Porto, Portugal;1. Department of Electronic, Computer Science and Automatic Engineering, “La Rábida” High Technical School of Engineering, University of Huelva, Spain;2. Department of Mathematics, “La Rábida” High Technical School of Engineering, University of Huelva, Spain
Abstract:This paper proposes an efficient combination of algorithms for the automated localization of the optic disc and macula in retinal fundus images. There is in fact no reason to assume that a single algorithm would be optimal. An ensemble of algorithms based on different principles can be more accurate than any of its individual members if the individual algorithms are doing better than random guessing. We aim to obtain an improved optic disc and macula detector by combining the prediction of multiple algorithms, benefiting from their strength and compensating their weaknesses. The location with maximum number of detectors’ outputs is formally the hotspot and is used to find the optic disc or macula center. An assessment of the performance of integrated system and detectors working separately is also presented. Our proposed combination of detectors achieved overall highest performance in detecting optic disc and fovea closest to the manually center chosen by the retinal specialist.
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