Automatic detection and characterisation of retinal vessel tree bifurcations and crossovers in eye fundus images

Computer Methods and Programs in Biomedicine
David CalvoJose Rouco

Abstract

Analysis of retinal vessel tree characteristics is an important task in medical diagnosis, specially in cases of diseases like vessel occlusion, hypertension or diabetes. The detection and classification of feature points in the arteriovenous eye tree will increase the information about the structure allowing its use for medical diagnosis. In this work a method for detection and classification of retinal vessel tree feature points is presented. The method applies and combines imaging techniques such as filters or morphologic operations to obtain an adequate structure for the detection. Classification is performed by analysing the feature points environment. Detection and classification of feature points is validated using the VARIA database. Experimental results are compared to previous approaches showing a much higher specificity in the characterisation of feature points while slightly increasing the sensitivity. These results provide a more reliable methodology for retinal structure analysis.

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Citations

Mar 5, 2013·Computers in Biology and Medicine·Abdolhossein FathiFardin Abdali Mohammadi
Jun 4, 2014·Computer Methods and Programs in Biomedicine·Shih-Feng Yang, Ching-Hsue Cheng
Feb 16, 2013·Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society·M M FrazS A Barman
Jun 18, 2017·Medical & Biological Engineering & Computing·Joaquim de MouraMarcos Ortega
Oct 27, 2015·Biomedical Papers of the Medical Faculty of the University Palacký, Olomouc, Czechoslovakia·T R Ganesh BabuR Venkatesh
Jul 26, 2019·PloS One·Pablo AmilCristina Masoller
May 31, 2019·Journal of Digital Imaging·Joaquim de MouraMarcos Ortega
Jul 18, 2020·Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society·A NouriR Redon

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