摘要
脑组织自动提取是脑功能分析中一个重要的预处理步骤,为提高脑组织提取的精度,提出了一种新的提取方法。该方法首先对磁共振成像(MRI)图像使用改进脑组织提取工具(BET)算法快速提取初始轮廓;其次对此初始轮廓进行数学形态学膨胀处理,得到初始感兴趣区域;然后在初始感兴趣区域中使用改进混合轮廓模型进行处理,得到新的轮廓线再进行膨胀处理得到新的区域,如此不断迭代;最后,该混合模型收敛,获得较精确脑组织轮廓。实验采用了7组来自IBSR网站的MRI数据序列,所提算法得到的平均错误划分比例为7.89%。实验结果表明所提方法对于脑组织提取精度的提高是有效和可行的。
Automatic extraction of brain is an important step in the preprocessing of brain internal analysis. To improve the extraction result, a modified Brain Extraction Tool （BET） and hybrid level set model based method for automatic brain extraction was proposed. The first step of the proposed method was obtaining rough brain boundary with the improved BET algorithm. Then the morphological expansion was operated on the rough brain boundary to initialize the Region of Interest （ROI） where the hybrid active contour model was defined to obtain a new contour. The ROI and the new contour were iteratively replaced until the accurate brain boundary was achieved. Seven Magnetic Resonance Imaging （MRI） volumes from Internet Brain Segmentation Repository （IBSR） website were used in the experiment. The proposed method achieved low average total misclassification ratio of 7.89%. The experimental results show the proposed method is effective and feasible.
出处
《计算机应用》
CSCD
北大核心
2013年第7期2014-2017,共4页
journal of Computer Applications
基金
国家自然科学基金资助项目(61162023)
江西省自然科学基金资助项目(20114BAB211023)
关键词
脑组织提取
混合水平集
脑组织提取工具
brain extraction hybrid level set Brain Extraction Tool （BET）
