中文摘要：

当前对白质损伤分割研究的缺陷就是不能真正用于实时分割任务,其主要原因是所用特征的表现性能较低.针对此问题,提出了新的数据处理方法和损伤分割特征.方法通过划分数据减少处理数据量的同时采用分治策略,区分处理白质灰质区域,从而改善了整体白质损伤分割的性能.在ACCORD-MIND MRI数据集上,使用SVM分类器将该新特征和传统特征的分割性能作了比较.实验结果表明,该特征在白质损伤分割中优于传统的特征,并能获得较好的分割结果和较快的分割速度.

英文摘要：

The shortage of current algorithm of White Matter Lesion Segmentation is not really can be used in realtime tasks.The main reason is the low performance characteristics to be used.To solve this problem,this paper proposes a new White Matter Lesion Segmentation feature and method of data processing to improve the performance of the White Matter Lesion Segmentation.This method uses Divide and Conquer and treats WM and GM differently.With the ACCORD-MIND data set of MRI and SVM classifier,we compare this new algorithm with traditional segmentation performance.The experimental results show that this feature is superior to the traditional features,and can obtain good segmentation results and fast segmentation speed.