Automatic segmentation and measurement of vasculature in retinal fundus images using probabilistic formulation.
Comput Math Methods Med
; 2013: 260410, 2013.
Article
en En
| MEDLINE
| ID: mdl-24382979
ABSTRACT
The automatic analysis of retinal blood vessels plays an important role in the computer-aided diagnosis. In this paper, we introduce a probabilistic tracking-based method for automatic vessel segmentation in retinal images. We take into account vessel edge detection on the whole retinal image and handle different vessel structures. During the tracking process, a Bayesian method with maximum a posteriori (MAP) as criterion is used to detect vessel edge points. Experimental evaluations of the tracking algorithm are performed on real retinal images from three publicly available databases STARE (Hoover et al., 2000), DRIVE (Staal et al., 2004), and REVIEW (Al-Diri et al., 2008 and 2009). We got high accuracy in vessel segmentation, width measurements, and vessel structure identification. The sensitivity and specificity on STARE are 0.7248 and 0.9666, respectively. On DRIVE, the sensitivity is 0.6522 and the specificity is up to 0.9710.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Retina
/
Vasos Retinianos
/
Fondo de Ojo
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Comput Math Methods Med
Asunto de la revista:
INFORMATICA MEDICA
Año:
2013
Tipo del documento:
Article
País de afiliación:
Francia