Title :
An improved AntTree algorithm for MRI brain segmentation
Author :
Chenling, Li ; Wenhua, Zeng ; Jiahe, Zhuang
Author_Institution :
Software Sch., Xiamen Univ., Xiamen
Abstract :
In this paper, an improved method is proposed based on the AntTree algorithm to deal with MRI brain segmentation. This algorithm uses a new tree-structure model to accelerate the calculation of segmenting the brain structure into brain structure, while matter, grey matter, and cerebrospinal fluid. The experimental results indicated that this new approach has made full usage of the pixels information of MRI. Compared with K-means algorithm and FCM algorithm, the results show that the improved AntTree algorithm is characterized by faster, robustness and accurateness.
Keywords :
biomedical MRI; brain; fuzzy set theory; image segmentation; medical image processing; pattern clustering; trees (mathematics); AntTree algorithm; K-means algorithm; MRI brain segmentation; cerebrospinal fluid; fuzzy c-means algorithm; magnetic resonance imaging; pixel information; Biomedical imaging; Brain modeling; Clustering algorithms; Feature extraction; Image segmentation; Magnetic resonance imaging; Pathology; Pixel; Robustness; Software algorithms;
Conference_Titel :
IT in Medicine and Education, 2008. ITME 2008. IEEE International Symposium on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-3616-3
Electronic_ISBN :
978-1-4244-2511-2
DOI :
10.1109/ITME.2008.4743952
