Aligned fibrillar scaffolds (AFSs) have been widely studied for their application in regenerative medicine, providing possible transplantable tissue replacements for nerve, spinal cord, tendon, ligament, muscle, etc. However, researches in AFSs are technically challenging mainly due to the complex fabrication and characterization processes, especially when the AFSs are made to be fully three-dimensional (3D). As the structure is linked to the quality and function of the engineered tissue product, there is an urgent need for novel techniques to characterize AFSs non-invasively and non-destructively and to link their characteristics to their functions and outcome. In this thesis AFS fabrication and characterization were explored. By combining second harmonic generation (SHG) imaging, multiphoton microscopy (MPM), and various image processing tools, the whole process of 3D tissue characterization could be achieved in a non-invasive, precise, and quantitative way. A proof-of-concept AFS with blended fibers made of polycaprolactone and porcine gelatin was used to demonstrate the feasibility of implementing such a strategy. The data indicated that, in terms of scaffold characterization, the proposed MPM method was capable of measuring the porosity of homogenous scaffolds precisely from deconvolved 3D images. Furthermore, the method could also be used to illustrate the orientation of the aligned nanofibers. Next, when SH-SY5Y neurons were cultured on the AFS, the MPM imaging was capable of evaluating the cell viability ratio, cell-localization in AFS, and neurite outgrowth. This provided guidance for selecting the alignment method for AFS functional recovery. Lastly, when employing this non-invasive imaging-based characterization method, it was possible to illustrate the relationship between the alignment of collagen arrays in decellularized corneal stroma and the transparency. In summary, the proposed strategy can provide some essential scaffold/tissue properties (such as alignment of fiber, porosity of scaffold, and cell viability ratio) quantitatively and non-invasively, which will help both scaffold processing design and characterization.