Study of Brain Contour Extraction Algorithm using MRI Images
Electroencephalogram EEG and MEG research are the non-invasive brain imaging techniques. The main research measured by the scalp EEG or MEG brain source signals can obtain three-dimensional quantitative information. Structure to match with the actual situation is the first model to solve EEG forward, the inverse problem of the clinical effectiveness of pre-conditions and key. Model of the head and the head are on the premise for the brain magnetic resonance image contour extraction and segmentation. Since the first complex internal structure, the access to the brain volume data segmentation is more difficult. In this paper, we propose a simulated annealing-based deformable model method and realize the head T2 weighted magnetic resonance images of the cross-sectional area of the extraction of the brain. To avoid falling into the local minimum in the deformation of the deformable model, we use a simulated annealing process of thinking, making the algorithm with the global search capability. The experim ental results show that the improved algorithm is effective and robust.
image segmentation deformable models GVF snake algorithm
Yuehua Wang Yili Fu
School of Mechatronics Engineering. Harbin institute of Technology,, Harbin, China Department ofNeu School of Mechatronics Engineering. Harbin institute of Technology,, Harbin, China
国际会议
海口
英文
69-72
2011-07-15（万方平台首次上网日期，不代表论文的发表时间）