Abstract
Validations about contour detection for segmentation in medical images are traditionally carried out by visual human inspection. In this context, automatic and formal validation of results becomes essential. A formal non parametric statistical framework for validation of vessel detection in medical images is presented. To obtain a formal validation of the segmentation process, a statistical test about the vessel contour is developed. The test proposed measures the way that the obtained (segmented) vessel fits in the theoretical vessel model avoiding the human inspection used in other methods. This test is used in this paper to validate a segmentation method for vessel detection in medical images that cope with high noisy images for mammograms. Results in this paper show that our segmentation model is validated for vessel detection with a signification value less than 0.05.
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Valverde, F.L., Guil, N., Domínguez, E., Muñoz, J. (2004). A Statistical Validation of Vessel Segmentation in Medical Images. In: Lemaître, C., Reyes, C.A., González, J.A. (eds) Advances in Artificial Intelligence – IBERAMIA 2004. IBERAMIA 2004. Lecture Notes in Computer Science(), vol 3315. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30498-2_62
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DOI: https://doi.org/10.1007/978-3-540-30498-2_62
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