Segmentation of retinal blood vessels by combining the detection of centerlines and morphological reconstruction

• Tipo: Artigo em Revista Científica Internacional
• Data: 2006

Autores

Ana Maria Mendonca (Autor) FEUP; Aurelio Campilho (Autor) FEUP

Revista

Título: IEEE Transactions on Medical Imaging

Vol. 25 Nº 9

Páginas: 1200-1213

ISSN: 0278-0062

Editora: IEEE

Indexação

ISI Web of Knowledge - 616 Citações

ISI Web of Science

Scopus - 785 Citações

COMPENDEX

Pubmed / Medline

INSPEC

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Biotecnologia ambiental

CORDIS: Ciências Tecnológicas > Tecnologia > Tecnologia médica

Outras Informações

ID Authenticus: P-004-HHD

DOI: 10.1109/tmi.2006.879955

Abstract (EN): This paper presents an automated method for the segmentation of the vascular network in retinal images. The algorithm starts with the extraction of vessel centerlines, which are used as guidelines for the subsequent vessel filling phase. For this purpose, the outputs of four directional differential operators are processed in order to select connected sets of candidate points to be further classified as centerline pixels using vessel derived features. The final segmentation is obtained using an iterative region growing method that integrates the contents of several binary images resulting from vessel width dependent morphological filters. Our approach was tested on two publicly available databases and its results are compared with recently published methods. The results demonstrate that our algorithm outperforms other solutions and approximates the average accuracy of a human observer without a significant degradation of sensitivity and specificity.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 14