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

By J. Lowell, Andrew Hunter, D. Steel, A. Basu, R. Ryder and R. L. Kennedy


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

Topics: G400 Computer Science, G740 Computer Vision
Year: 2004
DOI identifier: 10.1109/TMI.2004.830524
OAI identifier:

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  1. (1936). A method of estimating the calibre of retinal arteries in the living eye by means of opthalmoscope, illustrated results in some normal and pathological cases,” Trans.
  2. (1994). Accurate vessel width measurement from fundus photographs: a new concept,” doi
  3. (2000). Automated grading of venous beading,” doi
  4. (2004). Comparison of methods of measuring vessel widths on retinal photographs and doi
  5. (2001). Computer algorithms for the automated measurements of retinal arteriolar diameters,”
  6. (2002). Detection and measurement of retinal vessels in fundus images using amplitude modified second-order gaussian filter,” doi
  7. (1989). Detection of blood vessels in retinal images using two-dimensional matched filters,” doi
  8. (1991). Early treatment diabetic retinopathy study research group, “Fundus photographic risk factors for progression of diabetic retinopathy,” doi
  9. (2000). Locating the blood vessels in retinal images by piecewise threshold probing of a matched filter response,” doi
  10. (1986). Microphotometry of the blood column and light streak on retinal vessels in fundus photographs,” doi
  11. (1995). Neural Networks for Pattern Recognition, Clarendon Press, doi
  12. (2002). Peripheral vascular disease is associated with abnormal arteriolar diameter relationships at bifurcations in the human retina,” doi
  13. (2000). Quantification and characterisation of artieries doi
  14. (2000). Quantitative measurement of changes in retinal vessel diameter in ocular fundus images,” doi
  15. (1999). Retinal arteriolar diameters and elevated blood pressure: the atherosclerosis risk in communities study,” doi
  16. (2001). Retinal microvascular abnormalities and incident stroke: the atherosclerosis risk in communities study,” doi
  17. (2001). Retinal microvascular abnormalities and their relationship with hypertension, cardiovascular disease and mortality,” doi
  18. (1966). Scanning densitometer for photographic fundus measurements,” doi
  19. Semi-automatic segmentation of vascular network images using a rotating structuring element (rose) with mathematical morphology and dual feature thresholding,” doi
  20. (1967). Signs in the fundus oculi and arterial hypertension. unconventional assessment and significance,”
  21. (1986). The apparent and true width of the blood column,” doi
  22. (1994). The detection and quantification of retinopathy using digital angiograms,” doi
  23. (1986). Theoretical relationships between light streak characteristics and optical properties of retinal vessels,” doi

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