A modular supervised algorithm for vessel segmentation in red-free retinal images

Authors:
Andrea Anzalone;Federico Bizzarri;Mauro Parodi;Marco Storace
Affiliations:
Biophysical and Electronic Engineering Department, University of Genoa, Via Opera Pia 11a, I-16145 Genova, Italy;Biophysical and Electronic Engineering Department, University of Genoa, Via Opera Pia 11a, I-16145 Genova, Italy;Biophysical and Electronic Engineering Department, University of Genoa, Via Opera Pia 11a, I-16145 Genova, Italy;Biophysical and Electronic Engineering Department, University of Genoa, Via Opera Pia 11a, I-16145 Genova, Italy
Venue:
Computers in Biology and Medicine
Year:
2008

Citing 11
Cited 2

Adaptive histogram equalization and its variations

Computer Vision, Graphics, and Image Processing
Contrast limited adaptive histogram equalization

Graphics gems IV
Scale-Space Theory in Computer Vision

Scale-Space Theory in Computer Vision
Convergence Properties of the Nelder--Mead Simplex Method in Low Dimensions

SIAM Journal on Optimization
Adaptive Local Thresholding by Verification-Based Multithreshold Probing with Application to Vessel Detection in Retinal Images

IEEE Transactions on Pattern Analysis and Machine Intelligence
3D Multi-scale line filter for segmentation and visualization of curvilinear structures in medical images

CVRMed-MRCAS '97 Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery
Multi-scale line segmentation with automatic estimation of width, contrast and tangential direction in 2D and 3D medical images

CVRMed-MRCAS '97 Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery
A review of vessel extraction techniques and algorithms

ACM Computing Surveys (CSUR)
Enhancing retinal image by the Contourlet transform

Pattern Recognition Letters
An improved matched filter for blood vessel detection of digital retinal images

Computers in Biology and Medicine
Model-based method for improving the accuracy and repeatability of estimating vascular bifurcations and crossovers from retinal fundus images

IEEE Transactions on Information Technology in Biomedicine

Blood vessel segmentation methodologies in retinal images - A survey

Computer Methods and Programs in Biomedicine
Common carotid artery condition recognition technology using waveform features extracted from ultrasound spectrum images

Journal of Systems and Software

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, a supervised algorithm for vessel segmentation in red-free images of the human retina is proposed. The algorithm is modular and made up of two fundamental blocks. The optimal values of two algorithm parameters are found out by maximizing proper measures of performances (MOPs) able to evaluate from a quantitative point of view the results provided by the proposed algorithm. The choice of the MOP allows one to tailor the solution to the specific image features to be emphasized. The performances of the algorithm are compared with those of other methods described in the literature. The simulation results show a good trade-off between quality and processing speed times. For instance, in terms of the maximum average accuracy (MAA), K value, and specificity (SP), the best performance outcomes are 0.9587, 0.8069 and 0.9477, respectively.