Retinal Blood Vessel Segmentation by Using Matched Filtering and Fuzzy C-means Clustering with Integrated Level Set Method for Diabetic Retinopathy Assessment

Author:

Memari NogolORCID,Ramli Abd Rahman,Saripan M. Iqbal Bin,Mashohor Syamsiah,Moghbel Mehrdad

Publisher

Springer Science and Business Media LLC

Subject

Biomedical Engineering,General Medicine

Reference71 articles.

1. Asad, A. H., & Hassaanien, A.-E. (2016). Retinal blood vessels segmentation based on bio-inspired algorithm. In Applications of Intelligent Optimization in Biology and Medicine (pp. 181–215): Springer.

2. Solkar, S. D., & Das, L. (2017). Survey on retinal blood vessels segmentation techniques for detection of diabetic retinopathy. Diabetes.

3. Niemeijer, M., Staal, J., van Ginneken, B., Loog, M., & Abramoff, M. D. (2004). Comparative study of retinal vessel segmentation methods on a new publicly available database. In SPIE medical imaging (Vol. 5370, pp. 648–656): SPIE.

4. Staal, J., Abràmoff, M. D., Niemeijer, M., Viergever, M. A., & Van Ginneken, B. (2004). Ridge-based vessel segmentation in color images of the retina. IEEE Transactions on Medical Imaging, 23(4), 501–509.

5. Soares, J. V., Leandro, J. J., Cesar, R. M., Jelinek, H. F., & Cree, M. J. (2006). Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification. IEEE Transactions on Medical Imaging, 25(9), 1214–1222.

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