Title :
An automated vessel segmentation of retinal images using multiscale vesselness
Author :
Abdallah, Mariem Ben ; Malek, Jihene ; Krissian, Karl ; Tourki, Rached
Author_Institution :
Electron. & Micro-Electron. Lab., Fac. of Sci. of Monastir, Monsatir, Tunisia
Abstract :
The ocular fundus image can provide information on pathological changes caused by local ocular diseases and early signs of certain systemic diseases, such as diabetes and hypertension. Automated analysis and interpretation of fundus images has become a necessary and important diagnostic procedure in ophthalmology. The extraction of blood vessels from retinal images is an important and challenging task in medical analysis and diagnosis. In this paper, we introduce an implementation of the anisotropic diffusion which allows reducing the noise and better preserving small structures like vessels in 2D images. A vessel detection filter, based on a multi-scale vesselness function, is then applied to enhance vascular structures.
Keywords :
Hessian matrices; eye; filtering theory; image denoising; image enhancement; image segmentation; medical image processing; patient diagnosis; anisotropic diffusion; diabetes; hypertension; medical analysis; medical diagnosis; multiscale vesselness function; ocular fundus image; ophthalmology diagnostic procedure; retinal image; vascular structure enhancement; vessel detection filter; vessel segmentation; Anisotropic magnetoresistance; Biomedical imaging; Blood vessels; Eigenvalues and eigenfunctions; Image segmentation; Pixel; Retina; Flux-based Anisotropic Diffusion; Ocular fundus image; blood vessels; multiscale vesselness;
Conference_Titel :
Systems, Signals and Devices (SSD), 2011 8th International Multi-Conference on
Conference_Location :
Sousse
Print_ISBN :
978-1-4577-0413-0
DOI :
10.1109/SSD.2011.5767376
