Retinal vessel centerline extraction using multiscale matched filters, confidence and edge measures.
IEEE Trans Med Imaging
; 25(12): 1531-46, 2006 Dec.
Article
em En
| MEDLINE
| ID: mdl-17167990
ABSTRACT
Motivated by the goals of improving detection of low-contrast and narrow vessels and eliminating false detections at nonvascular structures, a new technique is presented for extracting vessels in retinal images. The core of the technique is a new likelihood ratio test that combines matched-filter responses, confidence measures and vessel boundary measures. Matched filter responses are derived in scale-space to extract vessels of widely varying widths. A vessel confidence measure is defined as a projection of a vector formed from a normalized pixel neighborhood onto a normalized ideal vessel profile. Vessel boundary measures and associated confidences are computed at potential vessel boundaries. Combined, these responses form a six-dimensional measurement vector at each pixel. A training technique is used to develop a mapping of this vector to a likelihood ratio that measures the "vesselness" at each pixel. Results comparing this vesselness measure to matched filters alone and to measures based on the Hessian of intensities show substantial improvements, both qualitatively and quantitatively. The Hessian can be used in place of the matched filter to obtain similar but less-substantial improvements or to steer the matched filter by preselecting kernel orientations. Finally, the new vesselness likelihood ratio is embedded into a vessel tracing framework, resulting in an efficient and effective vessel centerline extraction algorithm.
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Base de dados:
MEDLINE
Assunto principal:
Vasos Retinianos
/
Algoritmos
/
Reconhecimento Automatizado de Padrão
/
Angiofluoresceinografia
/
Interpretação de Imagem Assistida por Computador
/
Aumento da Imagem
/
Retinoscopia
Tipo de estudo:
Diagnostic_studies
/
Evaluation_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2006
Tipo de documento:
Article