中文摘要：

为快速有效地检测脑肿瘤,提出一种基于3D自适应模板匹配算法的脑肿瘤快速检测方法。采用改进的BET（brain extraction tool）算法从磁共振颅脑图像中提取出脑实质;再从脑实质中提取出包含所有肿瘤结构的3D感兴趣区域,并采用圆形度等特征对这些3D感兴趣区域进行筛选,筛选后的3D感兴趣区域可能是脑肿瘤。以每个3D感兴趣区域的中间层为基本层建立3D模板,将建立的3D模板与原图像中相应位置的3D感兴趣区域进行匹配,根据匹配特征确定相应的阈值,将高于阈值的3D感兴趣区域标记为肿瘤区域。为评价算法的性能,采用包含124个肿瘤（3~15 mm）的23个临床病例对该方法进行测试,利用ROC（receiver operating characteristic）曲线对测试结果进行分析,结果显示,该方法的敏感性率为88.7097%,假阳性为16.03%。与近年来报道的模板匹配方法相比,检测性能有明显的提高。

英文摘要：

This paper presented a three-dimensional adaptive template matching algorithm to detect brain tumors from magnetic resonance images quickly. First,it removed skull and other non-brain tissues by the improved BET algorithm. Then it extracted the structures that contained all small tumors as ROIs（ region of interest）. After that,it screened all the ROIs by the circular degree and other features. Then it created a three-dimensional template conformed to tumor characteristics for each ROI.Finally,it marched the three-dimensional templates with the original images to calculate the similarity coefficient. Then it determined the threshold according to the matching characteristic. After that,it marked the three-dimensional ROI with the similarity coefficient which was higher than the threshold value as the tumor region. To evaluate the performance of the algorithm,this paper used 23 clinical cases which contained 124 tumors（ 3 ~ 15 mm） in different size to test the system,and used ROC curve to analysis the test results. According to the ROC curve,the sensibility reaches 88. 7097% and the false position is 16. 03%.Compared to other template matching methods,the algorithm has been significantly improved.