Comput. Biol. Med. - Retinal vessel extraction by matched filter with first-order derivative of Gaussian.

Tópicos

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Resumo

Accurate extraction of retinal blood vessels is an important task in computer aided diagnosis of retinopathy. The matched filter (MF) is a simple yet effective method for vessel extraction. However, a MF will respond not only to vessels but also to non-vessel edges. This will lead to frequent false vessel detection. In this paper we propose a novel extension of the MF approach, namely the MF-FDOG, to detect retinal blood vessels. The proposed MF-FDOG is composed of the original MF, which is a zero-mean Gaussian function, and the first-order derivative of Gaussian (FDOG). The vessels are detected by thresholding the retinal image's response to the MF, while the threshold is adjusted by the image's response to the FDOG. The proposed MF-FDOG method is very simple; however, it reduces significantly the false detections produced by the original MF and detects many fine vessels that are missed by the MF. It achieves competitive vessel detection results as compared with those state-of-the-art schemes but with much lower complexity. In addition, it performs well at extracting vessels from pathological retinal images.

Resumo Limpo

accur extract retin blood vessel import task comput aid diagnosi retinopathi match filter mf simpl yet effect method vessel extract howev mf will respond vessel also nonvessel edg will lead frequent fals vessel detect paper propos novel extens mf approach name mffdog detect retin blood vessel propos mffdog compos origin mf zeromean gaussian function firstord deriv gaussian fdog vessel detect threshold retin imag respons mf threshold adjust imag respons fdog propos mffdog method simpl howev reduc signific fals detect produc origin mf detect mani fine vessel miss mf achiev competit vessel detect result compar stateoftheart scheme much lower complex addit perform well extract vessel patholog retin imag

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