Three-dimensional (3-D) reconstruction of the coronary artery is important for the diagnosis and interventional treatment of cardiovascular diseases. In this paper, a novel mean composited external force back-projective composition model is proposed and integrated into the deformable model framework for the 3-D reconstruction of coronary arteries from multiple angiograms. The parametric snake evolves toward the real vascular centerline in 3-D space based on the integrated internal energy and composited external energy. In addition, a polynomial function is constructed to determine the diameter of the cross section of the vascular segments, which fully utilizes the back-projection information of multiple angiograms. The deformable and proposed methods are comparatively validated using phantom datasets and routine angiographic images with respect to space and reprojection Euclidean distance errors. The experimental results demonstrate the effectiveness and robustness of the proposed model, which can achieve a mean space error of 0.570 mm and a mean reprojection error of 0.351 mm. In addition, the influence of the angle difference to the reconstruction accuracy is discussed and validated on phantom datasets, which demonstrate that an angle difference of for any two angiograms is suitable for the 3-D reconstruction process.