In this preclinical study we propose a protocol for rapid 3D imaging and fully automated segmentation to create a standardized healthy ACL image database. The segmentation problem of the ACL is particularly challenging due to its poor contrast. Our protocol demonstrated promising fully-automated segmentation of the ACL. Thus, allowing us to have a 3D computational model of the ACL. Ongoing experimentation explores dynamic imaging of the ACL in motions of flexion-extension. Such work will improve understanding of in vivo knee mechanics with potential to inform treatment of different injuries related to the ACL.