A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge Detection and Ridge Detection with Automatic Scale Selection
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Muliscale Vessel Enhancement Filtering
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
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
Evaluation Methods in Biomedical Informatics (Health Informatics)
Evaluation Methods in Biomedical Informatics (Health Informatics)
A Comparative Study on Feature Selection for Retinal Vessel Segmentation Using FABC
CAIP '09 Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns
Automatic retinal image registration scheme using global optimization techniques
IEEE Transactions on Information Technology in Biomedicine
IEEE Transactions on Information Technology in Biomedicine
IEEE Transactions on Information Technology in Biomedicine
A novel approach to diagnose diabetes based on the fractal characteristics of retinal images
IEEE Transactions on Information Technology in Biomedicine
IEEE Transactions on Information Technology in Biomedicine
Robust model-based vasculature detection in noisy biomedical images
IEEE Transactions on Information Technology in Biomedicine
Hybrid retinal image registration
IEEE Transactions on Information Technology in Biomedicine
Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation
IEEE Transactions on Image Processing
CIBB'10 Proceedings of the 7th international conference on Computational intelligence methods for bioinformatics and biostatistics
WILF'11 Proceedings of the 9th international conference on Fuzzy logic and applications
Retinal vessel segmentation using a multi-scale medialness function
Computers in Biology and Medicine
Sparse Representation Classifier for microaneurysm detection and retinal blood vessel extraction
Information Sciences: an International Journal
ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part II
Blood vessel segmentation methodologies in retinal images - A survey
Computer Methods and Programs in Biomedicine
An approach to localize the retinal blood vessels using bit planes and centerline detection
Computer Methods and Programs in Biomedicine
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This paper presents a method for automated vessel segmentation in retinal images. For each pixel in the field of view of the image, a 41-D feature vector is constructed, encoding information on the local intensity structure, spatial properties, and geometry at multiple scales. An AdaBoost classifier is trained on 789 914 gold standard examples of vessel and nonvessel pixels, then used for classifying previously unseen images. The algorithm was tested on the public digital retinal images for vessel extraction (DRIVE) set, frequently used in the literature and consisting of 40 manually labeled images with gold standard. Results were compared experimentally with those of eight algorithms as well as the additional manual segmentation provided by DRIVE. Training was conducted confined to the dedicated training set from the DRIVE database, and feature-based AdaBoost classifier (FABC) was tested on the 20 images from the test set. FABC achieved an area under the receiver operating characteristic (ROC) curve of 0.9561, in line with state-of-the-art approaches, but outperforming their accuracy (0.9597 versus 0.9473 for the nearest performer).