Title :
Segmentation of Computed Tomography 3D Images Using Partial Differential Equations
Author :
Aleman-Flores, Miguel ; Alvarez, Luis ; Aleman-Flores, Patricia ; Fuentes-Pavón, Rafael
Author_Institution :
Dept. de Inf. y Sist., Univ. de Las Palmas de Gran Canaria, Las Palmas, Spain
fDate :
Nov. 28 2011-Dec. 1 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.
Keywords :
computerised tomography; filtering theory; image denoising; image enhancement; image reconstruction; image segmentation; medical image processing; partial differential equations; 3D reconstruction; computed tomography 3D images; contour refinement; edge preservation; image segmentation; medical image analysis; noise reduction filtering; partial differential equation; region enhancement; Computed tomography; Equations; Histograms; Image edge detection; Image segmentation; Noise reduction; Three dimensional displays; computed tomography; partial differential equations; segmentation;
Conference_Titel :
Signal-Image Technology and Internet-Based Systems (SITIS), 2011 Seventh International Conference on
Conference_Location :
Dijon
Print_ISBN :
978-1-4673-0431-3
DOI :
10.1109/SITIS.2011.38
