Vessel Boundary Delineation on Fundus Images Using Graph-Based Approach

This paper proposes an algorithm to measure the width of retinal vessels in fundus photographs using graph-based algorithm to segment both vessel edges simultaneously. First, the simultaneous two-boundary segmentation problem is modeled as a two-slice, 3-D surface segmentation problem, which is furt...

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Vydané v:	IEEE transactions on medical imaging Ročník 30; číslo 6; s. 1184 - 1191
Hlavní autori:	Xiayu Xu, Niemeijer, M, Qi Song, Sonka, M, Garvin, M K, Reinhardt, J M, Abramoff, M D
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.06.2011 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Biomedical imaging Blood vessels Boundaries Delineation Diabetic Retinopathy - pathology Discs Fluorescein Angiography - methods Graph-based segmentation Humans Image edge detection Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image segmentation Imaging, Three-Dimensional - methods Observers Pattern Recognition, Automated - methods Pixel Reproducibility of Results Retina retinal photography Retinal Vessels - pathology Retinoscopy - methods Segmentation Segments Sensitivity and Specificity vessel width measurement
ISSN:	0278-0062, 1558-254X, 1558-254X
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Abstract	This paper proposes an algorithm to measure the width of retinal vessels in fundus photographs using graph-based algorithm to segment both vessel edges simultaneously. First, the simultaneous two-boundary segmentation problem is modeled as a two-slice, 3-D surface segmentation problem, which is further converted into the problem of computing a minimum closed set in a node-weighted graph. An initial segmentation is generated from a vessel probability image. We use the REVIEW database to evaluate diameter measurement performance. The algorithm is robust and estimates the vessel width with subpixel accuracy. The method is used to explore the relationship between the average vessel width and the distance from the optic disc in 600 subjects.
AbstractList	This paper proposes an algorithm to measure the width of retinal vessels in fundus photographs using graph-based algorithm to segment both vessel edges simultaneously. First, the simultaneous two-boundary segmentation problem is modeled as a two-slice, 3-D surface segmentation problem, which is further converted into the problem of computing a minimum closed set in a node-weighted graph. An initial segmentation is generated from a vessel probability image. We use the REVIEW database to evaluate diameter measurement performance. The algorithm is robust and estimates the vessel width with subpixel accuracy. The method is used to explore the relationship between the average vessel width and the distance from the optic disc in 600 subjects. This paper proposes an algorithm to measure the width of retinal vessels in fundus photographs using graph-based algorithm to segment both vessel edges simultaneously. First, the simultaneous two-boundary segmentation problem is modeled as a two-slice, 3-D surface segmentation problem, which is further converted into the problem of computing a minimum closed set in a node-weighted graph. An initial segmentation is generated from a vessel probability image. We use the REVIEW database to evaluate diameter measurement performance. The algorithm is robust and estimates the vessel width with subpixel accuracy. The method is used to explore the relationship between the average vessel width and the distance from the optic disc in 600 subjects.This paper proposes an algorithm to measure the width of retinal vessels in fundus photographs using graph-based algorithm to segment both vessel edges simultaneously. First, the simultaneous two-boundary segmentation problem is modeled as a two-slice, 3-D surface segmentation problem, which is further converted into the problem of computing a minimum closed set in a node-weighted graph. An initial segmentation is generated from a vessel probability image. We use the REVIEW database to evaluate diameter measurement performance. The algorithm is robust and estimates the vessel width with subpixel accuracy. The method is used to explore the relationship between the average vessel width and the distance from the optic disc in 600 subjects.
Author	Qi Song Garvin, M K Reinhardt, J M Abramoff, M D Xiayu Xu Sonka, M Niemeijer, M
Author_xml	– sequence: 1 surname: Xiayu Xu fullname: Xiayu Xu organization: Dept. of Biomed. Eng., Univ. of Iowa, Iowa City, IA, USA – sequence: 2 givenname: M surname: Niemeijer fullname: Niemeijer, M organization: Depts. of Ophthalmology & Visual Sci. & Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA, USA – sequence: 3 surname: Qi Song fullname: Qi Song organization: Dept. of Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA, USA – sequence: 4 givenname: M surname: Sonka fullname: Sonka, M organization: Depts. of Ophthalmology & Visual Sci. & Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA, USA – sequence: 5 givenname: M K surname: Garvin fullname: Garvin, M K organization: Dept. of Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA, USA – sequence: 6 givenname: J M surname: Reinhardt fullname: Reinhardt, J M organization: Dept. of Biomed. Eng., Univ. of Iowa, Iowa City, IA, USA – sequence: 7 givenname: M D surname: Abramoff fullname: Abramoff, M D email: michael-abramoff@uiowa.edu organization: Depts. of Ophthalmology & Visual Sci., Biomed. Eng., Univ. of Iowa, Iowa City, IA, USA
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SubjectTerms	Algorithms Biomedical imaging Blood vessels Boundaries Delineation Diabetic Retinopathy - pathology Discs Fluorescein Angiography - methods Graph-based segmentation Humans Image edge detection Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image segmentation Imaging, Three-Dimensional - methods Observers Pattern Recognition, Automated - methods Pixel Reproducibility of Results Retina retinal photography Retinal Vessels - pathology Retinoscopy - methods Segmentation Segments Sensitivity and Specificity vessel width measurement
Title	Vessel Boundary Delineation on Fundus Images Using Graph-Based Approach
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