一种基于主动轮廓模型的心脏核磁共振图像分割方法

A Method for Segmenting Cardiac Magnetic Resonance Images Using Active Contours

提出一种基于主动轮廓模型的左室壁内、外膜分割方法.首先构造了主动轮廓模型的广义法向有偏梯度矢量流外力模型GNBGVF,作为对梯度矢量流(GVF)的改进,该外力场同时保持了切线方向和法线方向有偏的扩散,具有捕捉范围大、抗噪能力强,且在弱边界泄漏等问题上性能突出.就左室壁内膜的分割而言,考虑到左室壁的近似为圆形的特点,引入了圆形约束的能量项,有利于克服由于图像灰度不均、乳突肌等而导致的局部极小.对于左室壁外膜的分割,采用内膜的分割结果初始化,即通过重新组合梯度分量来构造外力场.该外力场能够克服原始梯度矢量流的不足,使得左室壁外膜边缘很弱时也能得到保持,可以自动、准确地分割外膜.实验结果表明,该方法能高效准确地分割左室壁内、外膜.

This paper presents a method for segmenting the endocardium and epicardium of the left ventricle in cardiac magnetic resonance images using active contours.It first proposes an external force for active contours,which is called as generalized normally biased GVF（GNBGVF）.As an improvement on gradient vector flow,the GNBGVF external force keeps the diffusion along the tangential direction of the isophotes and biases that along the normal direction simultaneously.Consequently,it possesses the advantages of enlarged capture range,noise resistance and weak boundary preserving.Considering that the left ventricle is roughly a circle,a shape constraint based on circle is adopted for segmentation of the endocardium,which conquers the unexpected local minimum stemming form image inhomogeneity and papillary muscle.As to segmentation of the epicardium,the gradient vector components are reconfigured to generate the external force field,namely,taking the final contour for endocardium as initialization.This external force can overcome the demerits of the original GVF and NGVF forces and maintain the epicardium boundaries even if the contrast between the myocardium and neighbor organs is very low.With these strategies,the Snake contour is reactivated to locate the epicardium automatically and accurately.The results show its effectiveness.