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

PLoS ONE

Volumn 7, Issue 3, 2012, Pages

  Bankhead, Peter ^a,b   Scholfield, C Norman ^a,c   McGeown, J Graham ^a   Curtis, Tim M ^a  

^a QUEEN'S UNIVERSITY BELFAST   (United Kingdom)

^b UNIVERSITY OF HEIDELBERG   (Germany)

^c NARESUAN UNIVERSITY   (Thailand)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ALGORITHM; ARTICLE; BLOOD VESSEL DIAMETER; CLASSIFIER; COMPUTER ANALYSIS; COMPUTER INTERFACE; CONTROLLED STUDY; DATA BASE; FALSE POSITIVE RESULT; IMAGE ANALYSIS; IMAGE PROCESSING; MEASUREMENT; MEASUREMENT ERROR; OPHTHALMOSCOPY; RETINA BLOOD VESSEL; RETINA FLUORESCEIN ANGIOGRAPHY; SEGMENTATION ALGORITHM; COMPARATIVE STUDY; FLUORESCENCE ANGIOGRAPHY; GROWTH, DEVELOPMENT AND AGING; HISTOLOGY; HUMAN; VALIDATION STUDY; WAVELET ANALYSIS;

ALGORITHMS; FLUORESCEIN ANGIOGRAPHY; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; RETINAL VESSELS; WAVELET ANALYSIS;

EID: 84858068946     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0032435     Document Type: Article

References (57)

1. Knudtson MD, Klein BEK, Klein R, Wong TY, Hubbard LD, et al. (2004) Variation associated with measurement of retinal vessel diameters at different points in the pulse cycle. Br J Ophthalmol 88: 57-61.
2. Patton N, Aslam TM, MacGillivray T, Deary IJ, Dhillon B, et al. (2006) Retinal image analysis: concepts, applications and potential. Prog Retin Eye Res 25: 99-127.
3. Fischer JG, Mewes H, Hopp HH, Schubert R, (1996) Analysis of pressurized resistance vessel diam- eter changes with a low cost digital image processing device. Comput Meth Prog Bio 50: 23-30.
4. Tyml K, Anderson D, Lidington D, Ladak HM, (2003) A new method for assessing arteriolar diameter and hemodynamic resistance using image analysis of vessel lumen. Am J Physiol Heart Circ Physiol 284: H1721-8.
5. Patton N, Aslam T, Macgillivray T, Pattie A, Deary IJ, et al. (2005) Retinal vascular image analysis as a potential screening tool for cerebrovascular disease: a rationale based on homology between cerebral and retinal microvasculatures. J Anat 206: 319-348.
6. Sun C, Wang JJ, Mackey DA, Wong TY, (2009) Retinal vascular caliber: Systemic, environmental, and genetic associations. Surv Ophthalmol 54: 74-95.
7. Wang JJ, Liew G, Klein R, Rochtchina E, Knudtson MD, et al. (2007) Retinal vessel diameter and cardiovascular mortality: pooled data analysis from two older populations. Eur Heart J 28: 1984-1992.
8. Hubbard LD, Brothers RJ, King WN, Clegg LX, Klein R, et al. (1999) Methods for evaluation of retinal microvascular abnormalities associated with hypertension/sclerosis in the atherosclerosis risk in communities study,. Ophthalmology 106: 2269-2280.
9. Pakter HM, Ferlin E, Fuchs SC, Maestri MK, Moraes RS, et al. (2005) Measuring arteriolar-to- venous ratio in retinal photography of patients with hypertension: Development and application of a new semi-automated method. Am J Hypertens 18: 417-421.
10. Wong TY, Knudtson MD, Klein R, Klein BEK, Meuer SM, et al. (2004) Computer-assisted mea- surement of retinal vessel diameters in the Beaver Dam Eye Study: methodology, correlation between eyes, and effect of refractive errors. Ophthalmology 111: 1183-1190.
11. Kirbas C, Quek F, (2003) Vessel extraction techniques and algorithms: a survey. pp. 238-245 In: Proceedings of the Third IEEE Symposium on Bioinformatics and Bioengineering.
12. Staal JJ, Abramoff MD, Niemeijer M, Viergever MA, van Ginneken B, (2004) Ridge-based vessel segmentation in color images of the retina. IEEE Trans Med Imaging 23: 501-509.
13. Soares JVB, Leandro JJG, Cesar Junior RM, Jelinek HF, Cree MJ, (2006) Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification. IEEE Trans Med Imaging 25: 1214-1222.
14. Niemeijer M, Staal J, van Ginneken B, Loog M, Abramoff M, (2004) Comparative study of retinal vessel segmentation methods on a new publicly available database. In: Fitzpatrick JM, Sonka M, editors. pp. 648-656 SPIE Medical Imaging. SPIE, volume 5370.
15. Ricci E, Perfetti R, (2007) Retinal blood vessel segmentation using line operators and support vector classification. IEEE Trans Med Imaging 26: 1357-1365.
16. Chaudhuri S, Chatterjee S, Katz N, Nelson M, Goldbaum M, (1989) Detection of blood vessels in retinal images using two-dimensional matched filters. IEEE Trans Med Imaging 8: 263-269.
17. Hoover AD, Kouznetsova V, Goldbaum M, (2000) Locating blood vessels in retinal images by piecewise threshold probing of a matched _lter response. IEEE Trans Med Imaging 19: 203-210.
18. Wu CH, Agam G, Stanchev P, (2007) A hybrid filtering approach to retinal vessel segmentation. pp. 604-607 In: 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.
19. Pajak R, (2003) Use of two-dimensional matched filters for estimating a length of blood vessels newly created in angiogenesis process. Opto-Electronics Review 11: 237-241.
20. Vermeer KA, Vos FM, Lemij HG, Vossepoel AM, (2004) A model based method for retinal blood vessel detection. Comput Biol Med 34: 209-219.
21. Martinez-Perez ME, Hughes AD, Thom SA, Bharath AA, Parker KH, (2007) Segmentation of blood vessels from red-free and uorescein retinal images. Med Image Anal 11: 47-61.
22. Mendonça AM, Campilho A, (2006) Segmentation of retinal blood vessels by combining the detection of centerlines and morphological reconstruction. IEEE Trans Med Imaging 25: 1200-1213.
23. Leandro JJG, Soares JVB, Cesar RM Jr, Jelinek HF, (2003) Blood vessels segmentation in non-mydriatic images using wavelets and statistical classifiers. pp. 262-269 In: Proceedings of the XVI Brazilian Symposium on Computer Graphics and Image Processing.
24. Al-Rawi M, Karajeh H, (2007) Genetic algorithm matched filter optimization for automated detection of blood vessels from digital retinal images. Comput Meth Prog Bio 87: 248-253.
25. Anzalone A, Bizzarri F, Parodi M, Storace M, (2008) A modular supervised algorithm for vessel segmentation in red-free retinal images. Comput Biol Med 38: 913-922.
26. Al-Diri B, Hunter A, Steel D, (2009) An active contour model for segmenting and measuring retinal vessels. IEEE Trans Med Imaging 28: 1488-1497.
27. Heneghan C, Flynn J, O'Keefe M, Cahill M, (2002) Characterization of changes in blood vessel width and tortuosity in retinopathy of prematurity using image analysis. Med Image Anal 6: 407-429.
28. Martinez-Perez ME, Highes AD, Stanton AV, Thorn SA, Chapman N, et al. (2002) Retinal vascular tree morphology: a semi-automatic quantification. IEEE Trans Biomed Eng 49: 912-917.
29. Couper DJ, Klein R, Hubbard LD, Wong TY, Sorlie PD, et al. (2002) Reliability of retinal photography in the assessment of retinal microvascular characteristics: the atherosclerosis risk in communities study. Am J Ophthalmol 133: 78-88.
30. Wong TY, Hubbard LD, Klein R, Marino EK, Kronmal R, et al. (2002) Retinal microvascular abnormalities and blood pressure in older people: the cardiovascular health study. Br J Ophthalmol 86: 1007-1013.
31. Schwenke DO, Pearson JT, Umetani K, Kangawa K, Shirai M, (2007) Imaging of the pulmonary circulation in the closed-chest rat using synchrotron radiation microangiography. J Appl Physiol 102: 787-793.
32. Grisan E, Pesce A, Giani A, Foracchia M, Ruggeri A, (2004) A new tracking system for the robust extraction of retinal vessel structure. pp. 1620-1623 Vol. 3 In: 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. volume 1.
33. Tramontan L, Grisan E, Ruggeri A, (2008) An improved system for the automatic estimation of the Arteriolar-to-Venular diameter Ratio (AVR) in retinal images. Conf Proc IEEE Eng Med Biol Soc pp. 3550-3553.
34. Xu X, Niemeijer M, Song Q, Sonka M, Garvin MK, et al. (2011) Vessel boundary delineation on fundus images using graph-based approach. IEEE Trans Med Imaging 30: 1184-91.
35. Al-Diri B, Hunter A, Steel D, Habib M, Hudaib T, et al. (2008) REVIEW- A data set for retinal vessel profiles. pp. 2262-2265 In: 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
36. Starck JL, Murtagh F, (2001) Astronomical image and signal processing. IEEE Signal Process Mag 18: 30-40.
37. Olivo-Marin JC, (2002) Extraction of spots in biological images using multiscale products. Pattern Recognit 35: 1989-1996.
38. Starck JL, Fadili J, Murtagh F, (2007) The undecimated wavelet decomposition and its reconstruction. IEEE Trans Signal Process 16: 297-309.
39. Lam L, Lee SW, Suen CY, (1992) Thinning methodologies - a comprehensive survey. IEEE Trans Pattern Anal Mach Intell 14: 869-885.
40. Lee ETY, (1989) Choosing nodes in parametric curve interpolation. Computer-Aided Design 21: 363-370.
41. Chapman N, Witt N, Gao X, Bharath AA, Stanton AV, et al. (2001) Computer algorithms for the automated measurement of retinal arteriolar diameters. Br J Ophthalmol 85: 74-79.
42. Heier H, Brinchmann-Hansen O, (1989) Reliable measurements from fundus photographs in the presence of focusing errors. Invest Ophthalmol Vis Sci 30: 674-677.
43. Kaushik S, Tan AG, Mitchell P, Wang JJ, (2007) Prevalence and associations of enhanced retinal arteriolar light reex: A new look at an old sign. Ophthalmology 114: 113-120.
44. Metelitsina TI, Grunwald JE, DuPont JC, Ying GS, Liu C, (2006) Effect of viagra on retinal vein diameter in AMD patients. Exp Eye Res 83: 128-132.
45. Brinchmann-Hansen O, Heier H, (1986) Theoretical relations between light streak characteristics and optical properties of retinal vessels. Ophthalmologica supplement 179: 33-37.
46. Li H, Hsu W, Lee ML, Wong TY, (2005) Automatic grading of retinal vessel caliber. IEEE Trans Biomed Eng 52: 1352-1355.
47. Lowell J, Hunter A, Steel D, Basu A, Ryder R, et al. (2004) Measurement of retinal vessel widths from fundus images based on 2-D modeling. IEEE Trans Med Imaging 23: 1196-1204.
48. Martinez-Perez M, Hughes AD, Thom SA, Parker KH, (2007) Improvement of a retinal blood vessel segmentation method using the Insight Segmentation and Registration Toolkit (ITK). Conf Proc IEEE Eng Med Biol Soc 2007: 892-895.
49. Alonso-Montes C, Vilarino DL, Dudek P, Penedo MG, (2008) Fast retinal vessel tree extraction: A pixel parallel approach. Int J Circ Theor App 36: 641-651.
50. Perfetti R, Ricci E, Casali D, Costantini G, (2007) Cellular neural networks with virtual template expansion for retinal vessel segmentation. IEEE Trans Circuits Syst Express Briefs 54: 141-145.
51. Gregson PH, Shen Z, Scott RC, Kozousek V, (1995) Automated grading of venous beading. Comput Biomed Res 28: 291-304.
52. Zhou L, Rzeszotarski M, Singerman L, Chokreff J, (1994) The detection and quantification of retinopathy using digital angiograms. IEEE Trans Med Imaging 13: 619-626.
53. Gao X, Bharath A, Stanton A, Hughes A, Chapman N, et al. (2001) A method of vessel tracking for vessel diameter measurement on retinal images. pp. 881-884 In: IEEE International Conference on Image Processing. volume 2.
54. Li H, Hsu W, Lee M, Wang H, (2003) A piecewise Gaussian model for profiling and differentiating retinal vessels. pp. I-1069-72 In: IEEE International Conference on Image Processing. volume 1.
55. Narasimha-Iyer H, Mahadevan V, Beach J, Roysam B, (2008) Improved Detection of the Central Reex in Retinal Vessels Using a Generalized Dual-Gaussian Model and Robust Hypothesis Testing. IEEE Trans Inf Technol Biomed 12: 406-410.
56. Garg S, Sivaswamy J, Chandra S, (2007) Unsupervised curvature-based retinal vessel segmentation. 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro pp. 344-347.
57. Espona L, Carreira MJ, Penedo MG, Ortega M, (2008) Retinal vessel tree segmentation using a deformable contour model. pp. 1-4 In: 19th International Conference on Pattern Recognition.