Accurate segmentation for right ventricles based on Multi-Atlas

A new image registration and fusion method based on Multi-Atlas was proposed in this thesis. It treats all Atlas images as a series of data nodes and clusters them through massage propagation to obtain different exemplars, then uses these exemplars to participate in the normal atlas segmentation, orders them based on the dice similar coefficient, iterate, gets the final accurate segmentation. In term of registration, three-step registration is adopted: first rigid registration, then affine registration and B spline registration. Besides, fusion strategy called Joint Label Fusion is used, which is first used for right ventricle. The method makes split operation by registration and fusion method based on Multi-Atlas image, corrects a Multi-Atlas label fusion error caused by the registration, thereby optimizes segmentation result.