DocumentCode
119829
Title
Image segmentation using active contour models and partial differential equations
Author
Livada, Caslav ; Leventic, Hrvoje ; Galic, Irena
Author_Institution
Fac. of Electr. Eng. in Osijek, Univ. of Osijek, Osijek, Croatia
fYear
2014
fDate
10-12 Sept. 2014
Firstpage
1
Lastpage
4
Abstract
This article displays benefits of image segmentation for purpose of 3D reconstruction. Medical images and in this case CT slices are being reconstructed in 3D space for better medical investigation. It is relatively hard to use raw images for 3D reconstruction, so certain areas are being singled out using active contour models. Partial Differential Equations (PDEs), as non-linear diffusion, are used for image denoising because CT images have large gradiental areas that need to be evened out.
Keywords
computerised tomography; image denoising; image reconstruction; image segmentation; medical image processing; partial differential equations; 3D reconstruction; CT slices; PDE; active contour models; image denoising; image segmentation; medical image reconstruction; nonlinear diffusion; partial differential equations; Active contours; Equations; Heart; Image edge detection; Image segmentation; Mathematical model; Three-dimensional displays; 3D reconstruction; Active Contours; MRI; Non linear-diffusion; PDEs;
fLanguage
English
Publisher
ieee
Conference_Titel
ELMAR (ELMAR), 2014 56th International Symposium
Conference_Location
Zadar
Type
conf
DOI
10.1109/ELMAR.2014.6923348
Filename
6923348
Link To Document