Please use this identifier to cite or link to this item:
http://hdl.handle.net/10553/46192
| Title: | Segmentation of computed tomography 3D images using partial differential equations | Authors: | Alemán-Flores, Miguel Alvarez, L Alemán-Flores, Patricia Fuentes-Pavón, Rafael |
UNESCO Clasification: | 220990 Tratamiento digital. Imágenes 32 Ciencias médicas 120601 Construcción de algoritmos 120602 Ecuaciones diferenciales 120326 Simulación |
Keywords: | Computed tomography Partial differential equations Segmentation |
Issue Date: | 2011 | Conference: | 7th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2011 | Abstract: | The analysis of medical images, such as Computed Tomography (CT) Images, increasingly requires an automatic processing for region enhancement, segmentation, 3D reconstruction and many other purposes. This paper presents a framework for performing these tasks using partial differential equations in 3D images. From a set of partial differential equations, we obtain a method for noise reduction filtering with edge preservation, region enhancement through the discrimination of the relevant density values, contour refinement and 3D reconstruction. | URI: | http://hdl.handle.net/10553/46192 | ISBN: | 978-1-4673-0431-3 9780769546353 |
DOI: | 10.1109/SITIS.2011.38 | Source: | Proceedings - 7th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2011 (6120671), p. 345-349 |
| Appears in Collections: | Actas de congresos |
Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.