Title :
A new image segmentation and smoothing model
Author :
Gao, Song ; Bui, Tien D.
Author_Institution :
Dept. of Comput. Sci., Concordia Univ., Montreal, Que., Canada
Abstract :
In this paper, we develop a new segmentation and smoothing model which has many advantages compared to Chan and Vese´s active contours model. In our method, the curve evolution partial differential equations (PDEs) for different level set functions are decoupled and solved separately. This decoupling of the motion equations of the level set functions not only speeds up the segmentation process significantly, it also removes the difficulties associated with the initialization of the level sets in Chan and Vese´s method. The proposed method can avoid the initial condition problem. Finally, we use in this paper the diffusion equation for denoising and therefore it can deal with very noisy images.
Keywords :
biomedical MRI; image denoising; image segmentation; medical image processing; partial differential equations; smoothing methods; curve evolution partial differential equations; diffusion equation; image denoising; image segmentation; image smoothing; level set functions; motion equations; Active contours; Computer science; Image processing; Image segmentation; Level set; Mathematical model; Noise reduction; Partial differential equations; Poisson equations; Smoothing methods;
Conference_Titel :
Biomedical Imaging: Nano to Macro, 2004. IEEE International Symposium on
Print_ISBN :
0-7803-8388-5
DOI :
10.1109/ISBI.2004.1398493