Abstract
We present a method for retinal blood vessel segmentation based upon the scale-space analysis of the first and second derivative of the intensity image which gives information about its topology and overcomes the problem of variations in contrast inherent in these images. We use the local maxima over scales of the magnitude of the gradient and the maximum principal curvature as the two features used in a region growing procedure. In the first stage, the growth is constrained to regions of low gradient magnitude. In the final stage this constraint is relaxed to allow borders between regions to be defined. The algorithm is tested in both red-free and fluorescein retinal images.
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CITATION STYLE
Elena Martínez-Pérez, M., Hughes, A. D., Stanton, A. V., Thom, S. A., Bharath, A. A., & Parker, K. H. (1999). Retinal blood vessel segmentation by means of scale-space analysis and region growing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1679, pp. 90–97). Springer Verlag. https://doi.org/10.1007/10704282_10
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