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Multiscale Blood Vessel Delineation Using B-COSFIRE Filters

Part of the Lecture Notes in Computer Science book series (LNIP,volume 9257)

Abstract

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 B-COSFIRE 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.

Keywords

  • Retinal Image
  • Vessel Segmentation
  • Vessel Tree
  • Drive Data
  • Prototype Pattern

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Correspondence to Nicola Strisciuglio .

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Strisciuglio, N., Azzopardi, G., Vento, M., Petkov, N. (2015). Multiscale Blood Vessel Delineation Using B-COSFIRE Filters. In: Azzopardi, G., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2015. Lecture Notes in Computer Science(), vol 9257. Springer, Cham. https://doi.org/10.1007/978-3-319-23117-4_26

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  • DOI: https://doi.org/10.1007/978-3-319-23117-4_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23116-7

  • Online ISBN: 978-3-319-23117-4

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