We propose a delineation algorithm that deals with bar-like structures of different thickness. Detection of linear structures is applicable to several fields ranging from medical images for segmentation of vessels to aerial images for delineation of roads or rivers. The proposed method is suited for any delineation problem and employs a set of BCOSFIRE filters selective for lines and line-endings of different thickness. We determine the most effective filters for the application at hand by Generalized Matrix Learning Vector Quantization (GMLVQ) algorithm. We demonstrate the effectiveness of the proposed method by applying it to the task of vessel segmentation in retinal images. We perform experiments on two benchmark data sets, namely DRIVE and STARE. The experimental results show that the proposed delineation algorithm is highly effective and efficient. It can be considered as a general framework for a delineation task in various applications.
CITATION STYLE
Strisciuglio, N., Azzopardi, G., Vento, M., & Petkov, N. (2015). Multiscale blood vessel delineation using B-COSFIRE filters. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9257, pp. 300–312). Springer Verlag. https://doi.org/10.1007/978-3-319-23117-4_26
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