Leveraging Multiscale Hessian-Based Enhancement With a Novel Exudate Inpainting Technique for Retinal Vessel Segmentation
- 1 June 2015
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Journal of Biomedical and Health Informatics
- Vol. 20 (4), 1129-1138
- https://doi.org/10.1109/jbhi.2015.2440091
Abstract
Accurate vessel detection in retinal images is an important and difficult task. Detection is made more challenging in pathological images with the presence of exudates and other abnormalities. In this paper, we present a new unsupervised vessel segmentation approach to address this problem. A novel inpainting filter, called neighborhood estimator before filling, is proposed to inpaint exudates in a way that nearby false positives are significantly reduced during vessel enhancement. Retinal vascular enhancement is achieved with a multiple-scale Hessian approach. Experimental results show that the proposed vessel segmentation method outperforms state-of-the-art algorithms reported in the recent literature, both visually and in terms of quantitative measurements, with overall mean accuracy of 95.62% on the STARE dataset and 95.81% on the HRF dataset.Funding Information
- EU Marie Curie Initial Training Network (ITN) REtinal VAscular Modelling
- Measurement And Diagnosis (REVAMMAD) (316990)
This publication has 31 references indexed in Scilit:
- Boosting Hand-Crafted Features for Curvilinear Structure Segmentation by Learning Context FiltersPublished by Springer Science and Business Media LLC ,2015
- Novel VAMPIRE algorithms for quantitative analysis of the retinal vasculaturePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2013
- An Ensemble Classification-Based Approach Applied to Retinal Blood Vessel SegmentationIEEE Transactions on Biomedical Engineering, 2012
- A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants-Based FeaturesIEEE Transactions on Medical Imaging, 2010
- An Active Contour Model for Segmenting and Measuring Retinal VesselsIEEE Transactions on Medical Imaging, 2009
- Retinal Blood Vessel Segmentation Using Line Operators and Support Vector ClassificationIEEE Transactions on Medical Imaging, 2007
- Genetic algorithm matched filter optimization for automated detection of blood vessels from digital retinal imagesComputer Methods and Programs in Biomedicine, 2007
- Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classificationIEEE Transactions on Medical Imaging, 2006
- Segmentation of Retinal Blood Vessels Using Scale-Space Features and K-Nearest Neighbour ClassifierPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2006
- Locating blood vessels in retinal images by piecewise threshold probing of a matched filter responseIEEE Transactions on Medical Imaging, 2000