Name
Title | ||
|---|---|---|
Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification. |
Abstract | ||
|---|---|---|
We present a method for automated segmentation of the vasculature in retinal images. The method produces segmenta- tions by classifying each image pixel as vessel or nonvessel, based on the pixel's feature vector. Feature vectors are composed of the pixel's intensity and two-dimensional Gabor wavelet transform re- sponses taken at multiple scales. The Gabor wavelet is capable of tuning to specific frequencies, thus allowing noise filtering and vessel enhancement in a single step. We use a Bayesian classifier with class-conditional probability density functions (likelihoods) described as Gaussian mixtures, yielding a fast classification, while being able to model complex decision surfaces. The probability dis- tributions are estimated based on a training set of labeled pixels obtained from manual segmentations. The method's performance is evaluated on publicly available DRIVE (Staal et al., 2004) and STARE (Hoover et al., 2000) databases of manually labeled images. On the DRIVE database, it achieves an area under the receiver op- erating characteristic curve of 0.9614, being slightly superior than that presented by state-of-the-art approaches. We are making our implementation available as open source MATLAB scripts for re- searchers interested in implementation details, evaluation, or de- velopment of methods. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/TMI.2006.879967 | IEEE Trans. Med. Imaging |
Keywords | Field | DocType |
gaussian processes,wavelet transform,feature vectors,image segmentation,noise filtering,learning artificial intelligence,image classification,receiver operating characteristic,receiver operator characteristic,probability,probability distribution,wavelet,indexing terms,bayesian classifier,feature vector,pattern recognition,roc curve,conditional probability,visual system,fundus,wavelet transforms,gabor wavelets | Computer vision,Feature vector,Naive Bayes classifier,Pattern recognition,Gabor wavelet,Computer science,Image segmentation,Pixel,Artificial intelligence,Contextual image classification,Wavelet transform,Wavelet | Journal |
Volume | Issue | ISSN |
25 | 9 | 0278-0062 |
Citations | PageRank | References |
366 | 12.45 | 27 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| João V. B. Soares | 1 | 551 | 21.31 |
| Jorge J. G. Leandro | 2 | 399 | 17.92 |
| Roberto M. Cesar, Jr. | 3 | 794 | 49.46 |
| Herbert F. Jelinek | 4 | 477 | 36.78 |
| Michael J. Cree | 5 | 617 | 45.67 |