Abstract
Ultrasound imaging segmentation is a common method used to help in the diagnosis in multiple medical disciplines. This medical image modality is particularly difficult to segment and analyze since the quality of the images is relatively low, because of the presence of speckle noise. In this paper we present a set of techniques, based on texture findings, to increase the quality of the images. We characterize the ultrasound image texture by a vector of responses to a set of Gabor filters. Also, we combine front-propagation and active contours segmentation methods to achieve a fast accurate segmentation with the minimal expert intervention.
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Alemán-Flores, M., Alemán-Flores, P., Álvarez-León, L., Esteban-Sánchez, M.B., Fuentes-Pavón, R., Santana-Montesdeoca, J.M. (2007). Texture-Based Filtering and Front-Propagation Techniques for the Segmentation of Ultrasound Images. In: Moreno Díaz, R., Pichler, F., Quesada Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2007. EUROCAST 2007. Lecture Notes in Computer Science, vol 4739. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75867-9_120
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DOI: https://doi.org/10.1007/978-3-540-75867-9_120
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75866-2
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