A Scale-Space Medialness Transform Based on Boundary Concordance Voting
Journal of Mathematical Imaging and Vision
Enhancing retinal image by the Contourlet transform
Pattern Recognition Letters
Journal of Signal Processing Systems
Retinal vessel extraction by matched filter with first-order derivative of Gaussian
Computers in Biology and Medicine
Multi-scale approach for retinal vessel segmentation using medialness function
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
FABC: retinal vessel segmentation using adaboost
IEEE Transactions on Information Technology in Biomedicine
Hi-index | 0.00 |
Recently, automated segmentation of retinal vessels in optic fundus images has been an important focus of much research. In this paper, we propose a multi-scale method to segment retinal vessels based on a weighted two-dimensional (2D) medialness function. The results of the medialness function are first multiplied by the eigenvalues of the Hessian matrix. Next, centerlines of vessels are extracted using noise reduction and reconnection procedures. Finally, vessel radii are estimated and retinal vessels are segmented. The proposed method is evaluated and compared with several recent methods using images from the DRIVE and STARE databases.