Multiscale Blood Vessel Delineation Using B-COSFIRE Filters
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.
KeywordsRetinal Image Vessel Segmentation Vessel Tree Drive Data Prototype Pattern
Unable to display preview. Download preview PDF.
- 7.Chutatape, O., Liu Zheng, Krishnan, S.: Retinal blood vessel detection and tracking by matched gaussian and kalman filters. In: Chang, H., Zhang, Y. (eds.) Proc. 20th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. (EMBS 1998), vol. 17, pp. 3144–9 (1998)Google Scholar
- 10.Joachims, T.: Estimating the generalization performance of an svm efficiently. In: Proceedings of the Seventeenth International Conference on Machine Learning, ICML 2000, pp. 431–438. Morgan Kaufmann Publishers Inc., San Francisco (2000)Google Scholar
- 17.Muduli, P., Pati, U.: A novel technique for wall crack detection using image fusion. In: 2013 International Conference on Computer Communication and Informatics (ICCCI), pp. 1–6, January 2013Google Scholar
- 18.Niemeijer, M., Staal, J., van Ginneken, B., Loog, M., Abramoff, M.: Comparative study of retinal vessel segmentation methods on a new publicly available database. In: Proc. of the SPIE - The International Society for Optical Engineering, Medical Imaging 2004, Image Processing, San Diego. CA, USA, February 16–19, 2004, pp. 648–56. (2004)Google Scholar