Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geodesic Saliency of Watershed Contours and Hierarchical Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing
Color Segmentation Applied to Study of the Angiogenesis. Part I
Journal of Intelligent and Robotic Systems
Color image segmentation for Bladder Cancer Diagnosis
Mathematical and Computer Modelling: An International Journal
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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 image segmentation of atherosclerotic lesions of the thoracic aorta. In such sense, we introduced an algorithm, which was very useful in order to obtain the markers of the atherosclerotic lesions. Images were pre-processed using the Gauss filter and a contrast enhancement. The obtained results by using our strategy were validated calculating the false negatives (FN) and false positives (FP) according to criterion of physicians, 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. These images will be subject to an additional morphometrical analysis in order to study automatically the atherosclerosis and its organic-consequences.