Abstract
The watersheds method is a powerful segmentation tool developed in mathematical morphology, which has the drawback of producing over-segmentation. In this paper, in order to prevent its over-segmentation, we present a strategy to obtain robust markers for atherosclerotic lesions segmentation of the thoracic aorta. In such sense, we introduced an algorithm, which was very useful in order to obtain the markers of atherosclerotic lesions. The obtained results by using our strategy were validated calculating the false negatives (FN) and false positives (FP) according to criterion of pathologists, where 0% for FN and less than 11% for FP were obtained. Extensive experimentation showed that, using real image data, the proposed strategy was very suitable for our application.
Keywords
- Original Image
- Image Segmentation
- Atherosclerotic Lesion
- Grayscale Image
- Catchment Basin
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Rodríguez, R., Pacheco, O. (2005). A Strategy for Atherosclerotic Lesions Segmentation. In: Sanfeliu, A., Cortés, M.L. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2005. Lecture Notes in Computer Science, vol 3773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11578079_19
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DOI: https://doi.org/10.1007/11578079_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29850-2
Online ISBN: 978-3-540-32242-9
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