title: Automated detection of dark and bright lesions in retinal images for early detection of diabetic retinopathy.
abstract: There is an ever-increasing interest in the development of automatic medical diagnosis systems due to the advancement in computing technology and also to improve the service by medical community. The knowledge about health and disease is required for reliable and accurate medical diagnosis. Diabetic Retinopathy (DR) is one of the most common causes of blindness and it can be prevented if detected and treated early. DR has different signs and the most distinctive are microaneurysm and haemorrhage which are dark lesions and hard exudates and cotton wool spots which are bright lesions. Location and structure of blood vessels and optic disk play important role in accurate detection and classification of dark and bright lesions for early detection of DR. In this article, we propose a computer aided system for the early detection of DR. The article presents algorithms for retinal image preprocessing, blood vessel enhancement and segmentation and optic disk localization and detection which eventually lead to detection of different DR lesions using proposed hybrid fuzzy classifier. The developed methods are tested on four different publicly available databases. The presented methods are compared with recently published methods and the results show that presented methods outperform all others.
authors.affiliation: Department of Computer Engineering, National University of Sciences and Technology, Rawalpindi, Pakistan. usmakram@gmail.com
authors.forename: Usman M
authors.initials: UM
authors.lastname: Akram
authors.forename: Shoab A
authors.initials: SA
authors.lastname: Khan
mesh_terms: D000465:Algorithms; D003930:Diabetic Retinopathy / Q000175:diagnosis* / Q000473:pathology; D042241:Early Diagnosis; D005122:Exudates and Transudates; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009898:Optic Disk / Q000473:pathology; D010363:Pattern Recognition, Automated; D012160:Retina / Q000473:pathology*
references.citation: IEEE Trans Med Imaging. 2004 Oct;23(10):1189-95
references.pmid: 15493687
references.citation: IEEE Trans Med Imaging. 2004 Apr;23(4):501-9
references.pmid: 15084075
references.citation: Br J Ophthalmol. 1999 Aug;83(8):902-10
references.pmid: 10413690
references.citation: J Med Syst. 2008 Apr;32(2):107-15
references.pmid: 18461814
references.citation: Diabetes. 2008 Apr;57(4):1131-5
references.pmid: 18192540
references.citation: Diabet Med. 2004 Jan;21(1):84-90
references.pmid: 14706060
references.citation: IEEE Trans Med Imaging. 2009 May;28(5):775-85
references.pmid: 19150786
references.citation: IEEE Trans Med Imaging. 2003 Aug;22(8):951-8
references.pmid: 12906249
references.citation: Diabet Med. 1997;14 Suppl 5:S1-85
references.pmid: 9450510
references.citation: Arch Ophthalmol. 1998 Mar;116(3):297-303
references.pmid: 9514482
references.citation: J Med Syst. 2011 Dec;35(6):1491-501
references.pmid: 20703768
references.citation: IEEE Trans Biomed Eng. 2004 Feb;51(2):246-54
references.pmid: 14765697
references.citation: IEEE Trans Med Imaging. 1989;8(3):263-9
references.pmid: 18230524
references.citation: IEEE Trans Med Imaging. 1994;13(4):619-26
references.pmid: 18218540
references.citation: IEEE Trans Med Imaging. 2006 Sep;25(9):1214-22
references.pmid: 16967806
references.citation: IEEE Trans Biomed Eng. 2006 Jun;53(6):1084-98
references.pmid: 16761836
references.citation: IEEE Trans Med Imaging. 2002 Oct;21(10):1236-43
references.pmid: 12585705
references.citation: Arch Ophthalmol. 2001 Apr;119(4):509-15
references.pmid: 11296016
references.citation: IEEE Trans Med Imaging. 2006 Sep;25(9):1200-13
references.pmid: 16967805