Segmentation of computed tomography 3D images using partial differential equations

Título:	Segmentation of computed tomography 3D images using partial differential equations
Autores/as:	Alemán-Flores, Miguel Alvarez, L Alemán-Flores, Patricia Fuentes-Pavón, Rafael
Clasificación UNESCO:	220990 Tratamiento digital. Imágenes 32 Ciencias médicas 120601 Construcción de algoritmos 120602 Ecuaciones diferenciales 120326 Simulación
Palabras clave:	Computed tomography Partial differential equations Segmentation
Fecha de publicación:	2011
Conferencia:	7th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2011
Resumen:	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
Fuente:	Proceedings - 7th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2011 (6120671), p. 345-349
Colección:	Actas de congresos

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