Abstract:A novel method for segmenting cardiac magnetic resonance images based on Snake model was proposed.An external force called extended neighborhood Sigmoid gradient vector flow ENSGVF was presented as the improvement of gradient vector flow (GVF) for Snake which has a good performance on deep and narrow concavity convergence

capture range and weak edge preserving.In terms of the segmentation of endocardium

and considering that the left ventricle is roughly a circle

a circle shape constraint was adopted on the basis of ENSGVF Snake models

which can eliminate the unexpected local minimum caused by image inhomogeneity and papillary muscle.For the segmentation of epicardium

making full use of the segmentation result of endocardium

a new external force field and a new shape constraint were constructed to achieve automatic precise segmentation.The experimental results showed that the proposed method can address the challenges of lake of edge inhomogeneity

image inhomogeneity

effect of papillary muscle

and improves the rate of accuracy.