Authors:
Luiz Carlos Rodrigues
and
Mauricio Marengoni
Affiliation:
Universidade Presbiteriana Mackenzie, Brazil
Keyword(s):
Retinal Images, Mathematical Morphology, Wavelets, Multi-scale Filter.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Early and Biologically-Inspired Vision
;
Image and Video Analysis
;
Medical Image Applications
;
Segmentation and Grouping
Abstract:
A digitized image captured by a fundus camera provides an effective, inexpensive and non-invasive resource
for the assessment of vascular damage caused by diabetes, arterial hypertension, hypercholesterolemia and
aging. These unhealthy conditions may have very serious consequence like hemorrhages, exudates, branch
retinal vein occlusion, leading to the partial or total loss of vision capabilities. This study has focus on the
computer vision techniques of image segmentation required for a completely automated assessment system
for the vascular conditions of the eye. The study here presented proposes a new algorithm based on wavelets
transforms and mathematical morphology for the segmentation of the optic disc and a Hessian based multi-scale
filtering to segment the vascular tree in color eye fundus photographs. The optic disc and vessel tree, are
both essential to the analysis of the retinal fundus image. The optic disc can be identified by a bright region
on the fundus image, for its
segmentation we apply Haar wavelets transform to obtain the low frequencies
representation of the image and then apply mathematical morphology to enhance the segmentation. The tree
vessel segmentation is achieved using a Hessian-based multi-scale filtering that, based on its second order
derivatives, explores the tubular shape of a blood vessel to classify the pixels as part, or not, of a vessel. The
proposed method is being developed and tested based on the DRIVE database, which contains 40 color eye
fundus images.
(More)