Literature DB >> 19163475

An improved system for the automatic estimation of the Arteriolar-to-Venular diameter Ratio (AVR) in retinal images.

Lara Tramontan1, Enrico Grisan, Alfredo Ruggeri.   

Abstract

The Arteriolar-to-Venular diameter Ratio (AVR), a parameter derived from vessel caliber measurements in a specific region of retinal images, is used as a descriptor of generalized arteriolar narrowing, an eye fundus sign often seen in patients affected by hypertensive or diabetic retinopathies. We developed an improved system to compute AVR in a totally automatic way. Images are at first enhanced to highlight the vessel network, which is then traced by a vessel tracking algorithm. From the detected vessel structure, the position of the optic disc is derived and the region inside which the AVR data are to be measured is determined. Vessels within this region are classified as either arteries or veins, their caliber is estimated and the AVR parameter is eventually computed. Improvements with respect to the previous version are related to post-processing algorithms to enhance vessel tracking and a totally new artery/vein discrimination technique. Results provided by the new system have been compared with manually derived AVR values on 20 eye fundus images, resulting in a final correlation coefficient of 0.88.

Entities:  

Mesh:

Year:  2008        PMID: 19163475     DOI: 10.1109/IEMBS.2008.4649972

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  8 in total

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Journal:  J Med Imaging (Bellingham)       Date:  2015-11-19

2.  Reliability of vessel diameter measurements with a retinal oximeter.

Authors:  Renata Blondal; Margret Kara Sturludottir; Sveinn Hakon Hardarson; Gisli Hreinn Halldorsson; Einar Stefánsson
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3.  Fast retinal vessel detection and measurement using wavelets and edge location refinement.

Authors:  Peter Bankhead; C Norman Scholfield; J Graham McGeown; Tim M Curtis
Journal:  PLoS One       Date:  2012-03-12       Impact factor: 3.240

4.  Are Retinal Vessels Calibers Influenced by Blood Pressure Measured at the Time of Retinography Acquisition?

Authors:  Sandra C Fuchs; Helena M Pakter; Marcelo K Maestri; Marina Beltrami-Moreira; Miguel Gus; Leila B Moreira; Manuel M Oliveira; Flavio D Fuchs
Journal:  PLoS One       Date:  2015-09-16       Impact factor: 3.240

Review 5.  A review on automatic analysis techniques for color fundus photographs.

Authors:  Renátó Besenczi; János Tóth; András Hajdu
Journal:  Comput Struct Biotechnol J       Date:  2016-10-06       Impact factor: 7.271

Review 6.  A Comprehensive Study of Retinal Vessel Classification Methods in Fundus Images.

Authors:  Maliheh Miri; Zahra Amini; Hossein Rabbani; Raheleh Kafieh
Journal:  J Med Signals Sens       Date:  2017 Apr-Jun

7.  Contact-free trans-pars-planar illumination enables snapshot fundus camera for nonmydriatic wide field photography.

Authors:  Benquan Wang; Devrim Toslak; Minhaj Nur Alam; R V Paul Chan; Xincheng Yao
Journal:  Sci Rep       Date:  2018-06-08       Impact factor: 4.379

8.  Automated method for identification and artery-venous classification of vessel trees in retinal vessel networks.

Authors:  Vinayak S Joshi; Joseph M Reinhardt; Mona K Garvin; Michael D Abramoff
Journal:  PLoS One       Date:  2014-02-12       Impact factor: 3.240

  8 in total

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