OPEN IN READ APP
JOURNAL ARTICLE

Texton-based segmentation of retinal vessels

Donald A Adjeroh, Umasankar Kandaswamy, J Vernon Odom
Journal of the Optical Society of America. A, Optics, Image Science, and Vision 2007, 24 (5): 1384-93
17429484
With improvements in fundus imaging technology and the increasing use of digital images in screening and diagnosis, the issue of automated analysis of retinal images is gaining more serious attention. We consider the problem of retinal vessel segmentation, a key issue in automated analysis of digital fundus images. We propose a texture-based vessel segmentation algorithm based on the notion of textons. Using a weak statistical learning approach, we construct textons for retinal vasculature by designing filters that are specifically tuned to the structural and photometric properties of retinal vessels. We evaluate the performance of the proposed approach using a standard database of retinal images. On the DRIVE data set, the proposed method produced an average performance of 0.9568 specificity at 0.7346 sensitivity. This compares well with the best-published results on the data set 0.9773 specificity at 0.7194 sensitivity [Proc. SPIE5370, 648 (2004)].

Full Text Links

Find Full Text Links for this Article

Discussion

You are not logged in. Sign Up or Log In to join the discussion.

Related Papers

Available on the App Store

Available on the Play Store
Remove bar
Read by QxMD icon Read
17429484
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"