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

• Type: Article in International Scientific Journal
• Date: 2006

Authors

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

Journal

Title: IEEE Transactions on Medical Imaging

Vol. 25 No. 9

Pages: 1200-1213

ISSN: 0278-0062

Publisher: IEEE

Indexing

ISI Web of Knowledge - 616 Citations

ISI Web of Science

Scopus - 785 Citations

COMPENDEX

Pubmed / Medline

INSPEC

Scientific classification

FOS: Engineering and technology > Environmental biotechnology

CORDIS: Technological sciences > Technology > Medical technology

Other information

Authenticus ID: 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 14