@inproceedings{d3ff15a0ebbe44c7a4e35147d48dc7e7,
title = "A fast geodesic active contour model for medical images segmentation using prior analysis",
abstract = "The deformable Geodesic Active Contour (GAC) method is one of the most important techniques used in object boundaries detection in images. In this work, we modify the automatic GAC technique by incorporating priori information extracted from the region of interest. We introduce a new stopping function to speed up convergence and improve accuracy. The proposed technique was applied to both synthetic and real medical images. We show an improvement in speed of more than 40\% together with an excellent accuracy compared to the traditional GAC model.",
keywords = "Boundary detection, Deformable models, Geometric Active Contour GAC, Medical image segmentation, Prior information, Snake",
author = "\{Al Sharif\}, \{Sharif M.S.\} and Mohamed Deriche and Nabil Maalej",
year = "2010",
doi = "10.1109/IPTA.2010.5586749",
language = "English",
isbn = "9781424472482",
series = "2010 2nd International Conference on Image Processing Theory, Tools and Applications, IPTA 2010",
pages = "300--305",
booktitle = "2010 2nd International Conference on Image Processing Theory, Tools and Applications, IPTA 2010",
}