Tagged Cardiac Magnetic Resonance Images Segmentation Using Texture Information
利用纹理信息的带标记线心脏核磁共振图像分割

Aiming to solve the problem of the strong gradient coming from the tagged lines in the tagged cardiac magnetic resonance images,a texture analysis method is proposed based on a detailed signal energy which uses the signal feature provided by the tagged line itself.It can effectively remove the influence of the tagged lines.The cardiac magnetic resonance images are characterized by the weak edges and strong noises.Geodesic active contour model to define the evolving curve,which is solved by the level set method.To extract the outer edges of the left ventricle,a distance constraint energy term is added to solve the problem of the edges' reak or default.Depending on this energy term,the feature edges which cannot be directly extracted by gradient or texture information can be well extracted.Experimental results and error analysis show that the proposed method in this paper can effectively extract the inner and outer boundaries of the left ventricle and also has high accuracy.