Comput Methods Programs Biomed - Automatic model-based tracing algorithm for vessel segmentation and diameter estimation.

Tópicos

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Resumo

An automatic algorithm capable of segmenting the whole vessel tree and calculate vessel diameter and orientation in a digital ophthalmologic image is presented in this work. The algorithm is based on a parametric model of a vessel that can assume arbitrarily complex shape and a simple measure of match that quantifies how well the vessel model matches a given angiographic image. An automatic vessel tracing algorithm is described that exploits the geometric model and actively seeks vessel bifurcation, without user intervention. The proposed algorithm uses the geometric vessel model to determine the vessel diameter at each detected central axis pixel. For this reason, the algorithm is fine tuned using a subset of ophthalmologic images of the publically available DRIVE database, by maximizing vessel segmentation accuracy. The proposed algorithm is then applied to the remaining ophthalmological images of the DRIVE database. The segmentation results of the proposed algorithm compare favorably in terms of accuracy with six other well established vessel detection techniques, outperforming three of them in the majority of the available ophthalmologic images. The proposed algorithm achieves subpixel root mean square central axis positioning error that outperforms the non-expert based vessel segmentation, whereas the accuracy of vessel diameter estimation is comparable to that of the non-expert based vessel segmentation.

Resumo Limpo

automat algorithm capabl segment whole vessel tree calcul vessel diamet orient digit ophthalmolog imag present work algorithm base parametr model vessel can assum arbitrarili complex shape simpl measur match quantifi well vessel model match given angiograph imag automat vessel trace algorithm describ exploit geometr model activ seek vessel bifurc without user intervent propos algorithm use geometr vessel model determin vessel diamet detect central axi pixel reason algorithm fine tune use subset ophthalmolog imag public avail drive databas maxim vessel segment accuraci propos algorithm appli remain ophthalmolog imag drive databas segment result propos algorithm compar favor term accuraci six well establish vessel detect techniqu outperform three major avail ophthalmolog imag propos algorithm achiev subpixel root mean squar central axi posit error outperform nonexpert base vessel segment wherea accuraci vessel diamet estim compar nonexpert base vessel segment

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