关键词: 核磁共振图像, 自适应参数, 核距离, 空间关系

Abstract: MRI（Magnetic Resonance Imaging） is easily affected by noise, and it has poor contrast along boundaries. MRI of brain tissue segmentation under the strong noise has always been a difficult problem, and it has attracted much attention. This paper puts forward a kind of algorithm using adaptive regularization parameters combined with spatial relation, which replaces the Euclidean distance by the Kernel distance for calculation, and segments the MR image under the strong noise, the robustness of segmentation is greatly improved. The main advantage is to define adaptive parameters for each point, and puts the parameters into two expressions of the objective function. And it not only reduces the number of parameters, but also enhances the segment result. Finally, combined with spatial relation, the segmentation is more accurate. The experiments show the proposed method improves the segmentation accuracy, detail retention and noise processing in brain.

Key words: Magnetic Resonance Imaging（MRI）, adaptive parameter, kernel distance, spatial relation