IEEE Transactions on Pattern Analysis and Machine Intelligence
Retinal Blood Vessel Segmentation by Means of Scale-Space Analysis and Region Growing
MICCAI '99 Proceedings of the Second International Conference on Medical Image Computing and Computer-Assisted Intervention
IEEE Transactions on Information Technology in Biomedicine
Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation
IEEE Transactions on Image Processing
Gray and color image contrast enhancement by the curvelet transform
IEEE Transactions on Image Processing
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This paper presents an efficient method for automatic extraction of blood vessels in retinal images to improve the detection of low contrast and narrow vessels. The proposed algorithm is composed of four steps: curvelet-based contrast enhancement, match filtering, curvelet-based edge extraction, and length filtering. In this base, after reconstruction of enhanced image from the modified curvelet coefficients, match filtering is used to intensify the blood vessels. Then we employ curvelet transform to segment vessels from its background and finally the length filtering is used to remove the misclassified pixels. The performance of algorithm is evaluated on DRIVE [1] databases and compared with those obtained from a hand-labeled ground truth. Since the curvelet transform is well-suited to handle curve discontinuities, we achieve an area under ROC curve of 0.9631 that demonstrates improved performance of proposed algorithm compared with known techniques.