A proposal to measure the similarity between retinal vessel segmentations images

Marco A. Escobar, José R. Guzmán Sepúlveda, Jorge R. Parra Michel, Rafael Guzmán Cabrera

Abstract


Introduction: We propose a novel approach for the assessment of the similarity of retinal vessel segmentation images that is based on linking the standard performance metrics of a segmentation algorithm, with the actual structural properties of the images through the fractal dimension.

Method: We apply our methodology to compare the vascularity extracted by automatic segmentation against manually segmented images.

Results: We demonstrate that the strong correlation between the standard metrics and fractal dimension is preserved regardless of the size of the subimages analyzed.

Discussion or Conclusion: We show that the fractal dimension is correlated to the segmentation algorithm’s performance and therefore it can be used as a comparison metric.


Keywords


image processing; segmentation; fractal dimension; similarity measurement

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References


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DOI: https://doi.org/10.21640/ns.v11i22.1872

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