Fast retinal vessel detection and measurement using wavelets and edge location refinement.

The relationship between changes in retinal vessel morphology and the onset and progression of diseases such as diabetes, hypertension and retinopathy of prematurity (ROP) has been the subject of several large scale clinical studies. However, the difficulty of quantifying changes in retinal vessels...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Peter Bankhead, C Norman Scholfield, J Graham McGeown, Tim M Curtis
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/26d0566caa3d4546a6b536802496b8ff
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:26d0566caa3d4546a6b536802496b8ff
record_format	dspace
spelling	oai:doaj.org-article:26d0566caa3d4546a6b536802496b8ff2021-11-18T07:25:34ZFast retinal vessel detection and measurement using wavelets and edge location refinement.1932-620310.1371/journal.pone.0032435https://doaj.org/article/26d0566caa3d4546a6b536802496b8ff2012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22427837/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203The relationship between changes in retinal vessel morphology and the onset and progression of diseases such as diabetes, hypertension and retinopathy of prematurity (ROP) has been the subject of several large scale clinical studies. However, the difficulty of quantifying changes in retinal vessels in a sufficiently fast, accurate and repeatable manner has restricted the application of the insights gleaned from these studies to clinical practice. This paper presents a novel algorithm for the efficient detection and measurement of retinal vessels, which is general enough that it can be applied to both low and high resolution fundus photographs and fluorescein angiograms upon the adjustment of only a few intuitive parameters. Firstly, we describe the simple vessel segmentation strategy, formulated in the language of wavelets, that is used for fast vessel detection. When validated using a publicly available database of retinal images, this segmentation achieves a true positive rate of 70.27%, false positive rate of 2.83%, and accuracy score of 0.9371. Vessel edges are then more precisely localised using image profiles computed perpendicularly across a spline fit of each detected vessel centreline, so that both local and global changes in vessel diameter can be readily quantified. Using a second image database, we show that the diameters output by our algorithm display good agreement with the manual measurements made by three independent observers. We conclude that the improved speed and generality offered by our algorithm are achieved without sacrificing accuracy. The algorithm is implemented in MATLAB along with a graphical user interface, and we have made the source code freely available.Peter BankheadC Norman ScholfieldJ Graham McGeownTim M CurtisPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 3, p e32435 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Peter Bankhead C Norman Scholfield J Graham McGeown Tim M Curtis Fast retinal vessel detection and measurement using wavelets and edge location refinement.
description	The relationship between changes in retinal vessel morphology and the onset and progression of diseases such as diabetes, hypertension and retinopathy of prematurity (ROP) has been the subject of several large scale clinical studies. However, the difficulty of quantifying changes in retinal vessels in a sufficiently fast, accurate and repeatable manner has restricted the application of the insights gleaned from these studies to clinical practice. This paper presents a novel algorithm for the efficient detection and measurement of retinal vessels, which is general enough that it can be applied to both low and high resolution fundus photographs and fluorescein angiograms upon the adjustment of only a few intuitive parameters. Firstly, we describe the simple vessel segmentation strategy, formulated in the language of wavelets, that is used for fast vessel detection. When validated using a publicly available database of retinal images, this segmentation achieves a true positive rate of 70.27%, false positive rate of 2.83%, and accuracy score of 0.9371. Vessel edges are then more precisely localised using image profiles computed perpendicularly across a spline fit of each detected vessel centreline, so that both local and global changes in vessel diameter can be readily quantified. Using a second image database, we show that the diameters output by our algorithm display good agreement with the manual measurements made by three independent observers. We conclude that the improved speed and generality offered by our algorithm are achieved without sacrificing accuracy. The algorithm is implemented in MATLAB along with a graphical user interface, and we have made the source code freely available.
format	article
author	Peter Bankhead C Norman Scholfield J Graham McGeown Tim M Curtis
author_facet	Peter Bankhead C Norman Scholfield J Graham McGeown Tim M Curtis
author_sort	Peter Bankhead
title	Fast retinal vessel detection and measurement using wavelets and edge location refinement.
title_short	Fast retinal vessel detection and measurement using wavelets and edge location refinement.
title_full	Fast retinal vessel detection and measurement using wavelets and edge location refinement.
title_fullStr	Fast retinal vessel detection and measurement using wavelets and edge location refinement.
title_full_unstemmed	Fast retinal vessel detection and measurement using wavelets and edge location refinement.
title_sort	fast retinal vessel detection and measurement using wavelets and edge location refinement.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/26d0566caa3d4546a6b536802496b8ff
work_keys_str_mv	AT peterbankhead fastretinalvesseldetectionandmeasurementusingwaveletsandedgelocationrefinement AT cnormanscholfield fastretinalvesseldetectionandmeasurementusingwaveletsandedgelocationrefinement AT jgrahammcgeown fastretinalvesseldetectionandmeasurementusingwaveletsandedgelocationrefinement AT timmcurtis fastretinalvesseldetectionandmeasurementusingwaveletsandedgelocationrefinement
_version_	1718423463359676416

Fast retinal vessel detection and measurement using wavelets and edge location refinement.

Ejemplares similares