Retinal vessel enhancement based on directional field

Motivated by the goal of improving detection of micro-vessels with low contrast, a new technique based on directional field is presented for enhancing vessels in retinal images. This technique consists of two steps: the estimation of directional field and the enhancement. We will make enhancement along the vascular direction and normalize the brightness of image in a single step. After estimating the directional field, the mean and variance values in a local neighborhood were calculated pixel-by-pixel, accordingly normalize and enhance the local neighborhood. In order to eliminate the artificial boundary between two adjacent areas, an anisotropic Gaussian kernel was introduced to weight the enhancement. The proposed method can obviously increase the contrast of retinal vessels. 20 retinal images were tested in our experiments, and the results demonstrate an effective vessel enhancement algorithm.

[1]  Ian J. Deary,et al.  Retinal image analysis: concepts, applications and potential , 2006 .

[2]  David Zhang,et al.  A New Approach to Automated Retinal Vessel Segmentation Using Multiscale Analysis , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[3]  J. Kanski Clinical Ophthalmology: A Systematic Approach , 1989 .

[4]  B. Roysam,et al.  Image processing algorithms for retinal montage synthesis, mapping, and real-time location determination , 1998, IEEE Transactions on Biomedical Engineering.

[5]  Sawasd Tantaratana,et al.  Separable Gabor filter realization for fast fingerprint enhancement , 2005, IEEE International Conference on Image Processing 2005.

[6]  Joachim Weickert,et al.  A Review of Nonlinear Diffusion Filtering , 1997, Scale-Space.

[7]  Tatijana Stosic,et al.  Multifractal analysis of human retinal vessels , 2006, IEEE Transactions on Medical Imaging.

[8]  Roberto Marcondes Cesar Junior,et al.  Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification , 2005, IEEE Transactions on Medical Imaging.

[9]  Hanif M Ladak,et al.  A new method for assessing arteriolar diameter and hemodynamic resistance using image analysis of vessel lumen. , 2003, American journal of physiology. Heart and circulatory physiology.

[10]  Bram van Ginneken,et al.  Segmentation of the Optic Disc, Macula and Vascular Arch in Fundus Photographs , 2007, IEEE Transactions on Medical Imaging.

[11]  Liang Zhou,et al.  The detection and quantification of retinopathy using digital angiograms , 1994, IEEE Trans. Medical Imaging.

[12]  A. Bharath,et al.  Computer algorithms for the automated measurement of retinal arteriolar diameters , 2001, The British journal of ophthalmology.

[13]  Francis K. H. Quek,et al.  Vessel extraction techniques and algorithms: a survey , 2003, Third IEEE Symposium on Bioinformatics and Bioengineering, 2003. Proceedings..

[14]  Sabih H. Gerez,et al.  Systematic Methods for the Computation of the Directional Fields and Singular Points of Fingerprints , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Anil K. Jain,et al.  Fingerprint Image Enhancement: Algorithm and Performance Evaluation , 1998, IEEE Trans. Pattern Anal. Mach. Intell..