Abstract
In this paper, the use of morphological contrast mappings and a method to quantify the contrast for segmenting magnetic resonance images (MRI) of the brain was investigated. In particular, contrast transformations were employed for detecting white matter in a frontal lobule of the brain. Since contrast mappings depend on several parameters (size, contrast, proximity criterion), a morphological method to quantify the contrast was proposed in order to compute the optimal parameter values. The contrast quantifying method, that employs the gradient luminance concept, enabled us to obtain an output image associated with a good visual contrast. Because the contrast mappings introduced in this article were defined under partitions generated by the flat zone notion, these transformations are connected. Therefore, the degradation of the output images by the formation of new contours was avoided. Finally, the ratio between white and grey matter was calculated and compared with manual segmentations.
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Mendiola-Santibañez, J.D., Terol-Villalobos, I.R., Fernández-Bouzas, A. (2004). Morphological Contrast Measure and Contrast Mappings: One Application to the Segmentation of Brain MRI. In: Monroy, R., Arroyo-Figueroa, G., Sucar, L.E., Sossa, H. (eds) MICAI 2004: Advances in Artificial Intelligence. MICAI 2004. Lecture Notes in Computer Science(), vol 2972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24694-7_63
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DOI: https://doi.org/10.1007/978-3-540-24694-7_63
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