基于局部统计信息的主动轮廓模型

灰度不均普遍存在于医学图像中,为了克服灰度不均对图像分割的影响,基于图像的局部统计信息,结合偏移场校正模型,建立了高斯分布的主动轮廓模型.引入水平集函数,并根据变分法原理,实现了该算法.最后利用新算法和经典算法作对比实验,结果表明,新算法对合成图像和真实图像的分割都取得了较好的结果,具有更强的鲁棒性.

An active contour model based on the local statistical information

Intensity inhomogeneity exists widely in medical images,and it is often a great challenge to accurately segment images with intensity inhomogeneity.This paper presents an active contour model based on Gaussian distributions,and combines it with the bias field model in order to overcome the influence of intensity inhomogeneity on image segmentation.The level-set function is introduced and the algorithm is implemented according to the variation principle.Finally,the proposed level-set method and the classical algorithm are compared.The results show that the proposed algorithm achieves good results in both synthetic and real image segmentation and has a stronger robustness.