关键词: 图像分割, 水平集, 偏移估计, MR图像

Abstract: Intensity inhomogeneity often exists in Magnetic Resonance (MR) images, which is due to the smooth bias field caused by the deficiency of the device. Traditional intensity-based segmentation algorithms often assume the uniform intensity belonging to the object and background, respectively. Therefore, these algorithms fail to successfully segment image with intensity inhomogeneity. This paper proposed a local region fitting model for simultaneous segmentation and bias correction. The model is built based on the intensity property in the local region to build an energy function with respect to the intensity, bias field function and the region indicating function. Then, this energy function was optimized with respect to the intensity, bias field and the indicating function, respectively. The segmentation and bias field estimation would be conducted simultaneously finally. The experimental results on the real MR brain images demonstrate the advantages of the proposed method over variational level set approach.

Key words: image segmentation, level set, bias correction, Magnetic Resonance (MR) image