title: Automated analysis of retinal vascular tortuosity on color retinal images.
abstract: Recent advances in medical imaging modality have enabled us to identify new features in retinal vasculature. One of the features is retinal vascular tortuosity which has been shown to become a predictive factor for cardiovascular diseases and diabetes. The changes in retinal vascular tortuosity might be a sign of severity or improvement of the disease. In this paper, we propose a new method for measuring retinal vascular tortuosity. We adopt a new technique to analyze tortuosity that consider vessel-segment's width simultaneously. Our proposed method measures vessel-segment's tortuosity on its edge. A qualitative assessment shows that the method is appropriate for measuring the tortuosity of the vessels in different widths and directions in the image. Finally, a comparison distinguishing tortuous vs. non tortuous vessels demonstrates that the proposed approach may be suitable for predicting or earlier diagnosis of diabetes or cardiovascular diseases.
authors: Department of Computer Science and Software Engineering, The University of Melbourne, Melbourne, Australia. abhuiyan@unimelb.edu.au
authors: Alauddin
authors: A
authors: Bhuiyan
authors: Baikunth
authors: B
authors: Nath
authors: Kotagiri
authors: K
authors: Ramamohanarao
authors: Ryo
authors: R
authors: Kawasaki
authors: Tien Yin
authors: TY
authors: Wong
mesh_terms: D003658:Decision Making, Computer-Assisted; D003920:Diabetes Mellitus / Q000503:physiopathology; D003941:Diagnostic Techniques, Ophthalmological; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D012164:Retinal Diseases / Q000175:diagnosis*; D012171:Retinal Vessels / Q000503:physiopathology*