Automatic detection and segmentation of brain tumor using fuzzy classification and deformable models
We propose a new general method for segmenting brain tumors in 3D magnetic resonance images. Our method is applicable to different types of tumors. First, the brain is segmented using a new approach, robust to the presence of tumors. Then a tumor detection is performed, based on improved fuzzy classification. Its result constitutes the initialization of a segmentation method based on a deformable model, leading to a precise segmentation of the tumors. Imprecision and variability are taken into account at all levels, using appropriate fuzzy models. The result obtained on different types of tumors have been evaluated by comparison with manual segmentations.
brain tumor segmentation deformable model improved kernel fuzzy c-mean
Wang Yang Ma Siliang
Dept. of Computational Mathematics Jilin University Changchun, China
国际会议
上海
英文
1692-1695
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）