Contour-based surface reconstruction in medical imaging refers to the reconstruction of a 3D surface from extracted contours from traditional medical imaging modalities such as HRCT or MRI scans. Reconstructed models from HRCT and MRI have a variety of applications including diagnosis, treatment planning, and educational purposes. A notable problem in contour-based surface reconstruction with considerable interest is the branching problem. This problem refers to the issues that arise when attempting to reconstruct branching structures that occur in human anatomy. This research introduces dynamic time warping as a solution to the problem of point correspondence in reconstruction to provide alignments between contours sampled from structures that are known to be problematic. Contour-based surface reconstruction in this application is difficult to test. Often it requires input from a medical practitioner as to whether a reconstruction is accurate or not. However, early testing can be done during development with synthetically generated models. This research provides quantitative analysis with the introduction of a technique for generation of test contour data from ground truth surfaces. The ground truth meshes used in this work represent commonly encountered cases in surface reconstruction. Results from comparative analysis show robustness in the proposed technique with variable levels of source contour information available.