Quantitative analysis of three dimentional (3D) blood flow direction and location will benefit and guide the surgical thinning and dissection process. Toward this goal, this study was performed to reconstruct 3D vascular trees with the incorporation of temporal information from contrast-agent propagation. A computational technique based on our previous work to segment the 3D vascular tree structure from the CT scan volume image sets was proposed. This technique utilizes the deformation method which is a moving grid methodology and which in tradition is used to improve the computational accuracy and efficiency in solving differential equations. Compared with our previous work, we extended the moving grid deformation method to 3D and incorporated 3D region growing method for an initial segmentation. At last, a 3D divergence operator was applied to delineate vascular tree structures from the 3D grid volume plot. Experimental results show the 3D nature of the vascular structure and four-dimensional (4D) vascular tree evolving process. The proposed computational framework demonstrates its effectiveness and improvement in the modeling of 3D vascular tree.