ISMDA '01 Proceedings of the Second International Symposium on Medical Data Analysis
An improved matched filter for blood vessel detection of digital retinal images
Computers in Biology and Medicine
Computer Methods and Programs in Biomedicine
Vessel enhancement filter using directional filter bank
Computer Vision and Image Understanding
Journal of Signal Processing Systems
Machine Graphics & Vision International Journal
Spatially-Variant Morpho-Hessian Filter: Efficient Implementation and Application
ISMM '09 Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing
IEEE Transactions on Information Technology in Biomedicine - Special section on biomedical informatics
Detection of the foveal avascular zone on retinal angiograms using Markov random fields
Digital Signal Processing
Maximum likelihood estimation of vessel parameters from scale space analysis
Image and Vision Computing
A robust approach for automatic detection and segmentation of cracks in underground pipeline images
Image and Vision Computing
An Automatic Hybrid Method for Retinal Blood Vessel Extraction
International Journal of Applied Mathematics and Computer Science - Selected Problems of Computer Science and Control
Retinal vessel extraction by matched filter with first-order derivative of Gaussian
Computers in Biology and Medicine
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Retinal vessel extraction by a combined neural network-wavelet enhancement method
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Statistical-based linear vessel structure detection in medical images
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Extraction of retinal blood vessels by curvelet transform
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Evaluation of retinal vessel segmentation methods for microaneurysms detection
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Determination of foveal avascular zone in diabetic retinopathy digital fundus images
Computers in Biology and Medicine
Unsupervised Fuzzy Based Vessel Segmentation In Pathological Digital Fundus Images
Journal of Medical Systems
Automatic model-based tracing algorithm for vessel segmentation and diameter estimation
Computer Methods and Programs in Biomedicine
FABC: retinal vessel segmentation using adaboost
IEEE Transactions on Information Technology in Biomedicine
Retinal vessel extraction with the image ray transform
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
Detection and matching of curvilinear structures
Pattern Recognition
Proceedings of the International Conference & Workshop on Emerging Trends in Technology
Vascular tree segmentation in retinal angiographies: deformable contour model approach
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
Morphological segmentation based on edge detection for sewer pipe defects on CCTV images
Expert Systems with Applications: An International Journal
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 extraction using first-order derivative of Gaussian and morphological processing
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
The image ray transform for structural feature detection
Pattern Recognition Letters
Journal of Medical Systems
ISCIS'06 Proceedings of the 21st international conference on Computer and Information Sciences
Extraction of blood vessels in ophthalmic color images of human retinas
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
ICMB'10 Proceedings of the Second international conference on Medical Biometrics
Computer vision algorithms for retinal image analysis: current results and future directions
CVBIA'05 Proceedings of the First international conference on Computer Vision for Biomedical Image Applications
Expert Systems with Applications: An International Journal
MFCA: matched filters with cellular automata for retinal vessel detection
MICAI'11 Proceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
Sparse Representation Classifier for microaneurysm detection and retinal blood vessel extraction
Information Sciences: an International Journal
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
Non-Compactness Attribute Filtering to Extract Retinal Blood Vessels in Fundus Images
International Journal of E-Health and Medical Communications
Computer-aided diagnosis of diabetic retinopathy: A review
Computers in Biology and Medicine
Hi-index | 0.02 |
This paper presents an algorithm based on mathematical morphology and curvature evaluation for the detection of vessel-like patterns in a noisy environment. Such patterns are very common in medical images. Vessel detection is interesting for the computation of parameters related to blood flow. Its tree-like geometry makes it a usable feature for registration between images that can be of a different nature. In order to define vessel-like patterns, segmentation is performed with respect to a precise model. We define a vessel as a bright pattern, piece-wise connected, and locally linear, mathematical morphology is very well adapted to this description, however other patterns fit such a morphological description. In order to differentiate vessels from analogous background patterns, a cross-curvature evaluation is performed. They are separated out as they have a specific Gaussian-like profile whose curvature varies smoothly along the vessel. The detection algorithm that derives directly from this modeling is based on four steps: (1) noise reduction; (2) linear pattern with Gaussian-like profile improvement; (3) cross-curvature evaluation; (4) linear filtering. We present its theoretical background and illustrate it on real images of various natures, then evaluate its robustness and its accuracy with respect to noise