Literature DB >> 15493688

Measurement of retinal vessel widths from fundus images based on 2-D modeling.

James Lowell1, Andrew Hunter, David Steel, Ansu Basu, Robert Ryder, R Lee Kennedy.   

Abstract

Changes in retinal vessel diameter are an important sign of diseases such as hypertension, arteriosclerosis and diabetes mellitus. Obtaining precise measurements of vascular widths is a critical and demanding process in automated retinal image analysis as the typical vessel is only a few pixels wide. This paper presents an algorithm to measure the vessel diameter to subpixel accuracy. The diameter measurement is based on a two-dimensional difference of Gaussian model, which is optimized to fit a two-dimensional intensity vessel segment. The performance of the method is evaluated against Brinchmann-Hansen's half height, Gregson's rectangular profile and Zhou's Gaussian model. Results from 100 sample profiles show that the presented algorithm is over 30% more precise than the compared techniques and is accurate to a third of a pixel.

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Year:  2004        PMID: 15493688     DOI: 10.1109/TMI.2004.830524

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  21 in total

1.  Impact of vessel diameter and bandwidth of illumination in sidestream dark-field oximetry.

Authors:  Tomohiro Kurata; Zhenguang Li; Shigeto Oda; Hiroshi Kawahira; Hideaki Haneishi
Journal:  Biomed Opt Express       Date:  2015-04-06       Impact factor: 3.732

2.  Application of morphological bit planes in retinal blood vessel extraction.

Authors:  M M Fraz; A Basit; S A Barman
Journal:  J Digit Imaging       Date:  2013-04       Impact factor: 4.056

3.  Vessel boundary delineation on fundus images using graph-based approach.

Authors:  Xiayu Xu; Meindert Niemeijer; Qi Song; Milan Sonka; Mona K Garvin; Joseph M Reinhardt; Michael D Abràmoff
Journal:  IEEE Trans Med Imaging       Date:  2011-01-06       Impact factor: 10.048

4.  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

5.  Modeling Photo-Bleaching Kinetics to Create High Resolution Maps of Rod Rhodopsin in the Human Retina.

Authors:  Martin Ehler; Julia Dobrosotskaya; Denise Cunningham; Wai T Wong; Emily Y Chew; Wojtek Czaja; Robert F Bonner
Journal:  PLoS One       Date:  2015-07-21       Impact factor: 3.240

6.  Automatic segmentation and measurement of vasculature in retinal fundus images using probabilistic formulation.

Authors:  Yi Yin; Mouloud Adel; Salah Bourennane
Journal:  Comput Math Methods Med       Date:  2013-12-08       Impact factor: 2.238

7.  Accurate image analysis of the retina using hessian matrix and binarisation of thresholded entropy with application of texture mapping.

Authors:  Xiaoxia Yin; Brian W-H Ng; Jing He; Yanchun Zhang; Derek Abbott
Journal:  PLoS One       Date:  2014-04-29       Impact factor: 3.240

8.  The reading of components of diabetic retinopathy: an evolutionary approach for filtering normal digital fundus imaging in screening and population based studies.

Authors:  Hongying Lilian Tang; Jonathan Goh; Tunde Peto; Bingo Wing-Kuen Ling; Lutfiah Ismail Al Turk; Yin Hu; Su Wang; George Michael Saleh
Journal:  PLoS One       Date:  2013-07-01       Impact factor: 3.240

9.  The clinical assessment of retinal microvascular structure and therapeutic implications.

Authors:  Alun D Hughes
Journal:  Curr Treat Options Cardiovasc Med       Date:  2007-06

10.  Retinal vessel diameter measurement using unsupervised linear discriminant analysis.

Authors:  Dinesh K Kumar; Behzad Aliahmad; Hao Hao
Journal:  ISRN Ophthalmol       Date:  2012-11-06
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