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

fYear

2011

fDate

Nov. 28 2011-Dec. 1 2011

Firstpage

345

Lastpage

349

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/SITIS.2011.38

Filename

6120671