Segmentation of optic disc and blood vessels in retinal images using wavelets, mathematical morphology and Hessian-based multi-scale filtering
Tipo
Artigo
Data de publicação
2017
Periódico
Biomedical Signal Processing and Control
Citações (Scopus)
95
Autores
Rodrigues L.C.
Marengoni M.
Marengoni M.
Orientador
Título da Revista
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Resumo
© 2017 Elsevier LtdThe high importance of the accurate and early diagnostic has motivated the development of computer vision techniques of image processing and segmentation required for an completely automated assessment system for the retinal conditions. In this study we present a new algorithm built on wavelets transforms and mathematical morphology for detecting the optic disc and we explore the tubular characteristic of the blood vessels to segment the retinal veins and arteries. Both, optic disc and vascular structure, are landmarks for image registration and are essential for the retinal image analysis. Instead of a manual try and error method to choose the best parameters for detecting vessels as accurately as possible, we used a genetic algorithm and its sequence of generations and crossovers. However the technique of exploring the tubular characteristic of the vessels reaches its limits when the vessels are represented by, sometimes not continuous, winding lines of 1 pixel. To overcome this limitation we adopted a graph based approach using Dijkstra's shortest path algorithm to track the segments and a statistic method of Student t distribution to assess whether or not the identified segment is part of the vascular structure. The proposed method was developed and tested on the Digital Retinal Images for Vessel Extraction (DRIVE) freely available database, which contains 40 annotated color eye fundus image.
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Assuntos Scopus
Computer vision techniques , Dijkstra's shortest path algorithm , Graphs , Multi-scale filtering , Retinal fundus images , Retinal image analysis , Student-t distribution , Wavelets