基于多模态局部转向核的脑部多发性硬化检测算法研究

容积效应和伪影现象是MR影像处理中的重要影响因素,单模态处理方法易受两者影响。提出一种改进的基于多模态局部转向核的方法来检测大脑中的多发性硬化。该方法利用多模态脑MR影像和大脑近似轴对称的先验知识来进行大脑情况的变化检测。局部转向核能够度量像素与其周围环境的相似程度,因此该方法将局部转向核作为特征,用余弦相似性来衡量差异性。实验结果表明,多模态的引入减少了容积效应和伪影现象,改善了检测效果。

Change Detection of Multiple Sclerosis in Brain Based on Multi-modal Local Steering Kernel

Volume effect and artifact are important influence factors in MR image processing and single-modal methods can be easily affected.This paper proposed an improved method based on multi-modal local steering kernel to detect the multiple sclerosis in the brain.This method utilizes multi-modal brain MR images and the approximate symmetry of the brain for change detection of the brain.Local steering kernel can measure the similarity between pixels and their surroundings.The proposed method takes the local steering kernel as the feature and measures the dissimilarity by cosine similarity.The experimental results show that the introduction of multi-modal reduces the volume effect and artifact in the MRI,improving the detection effect.