Image based strain measurement within whole bone structures can be used to better understand fracture risk under load. This project aims to apply feature registration algorithms to measure strain using µCT images of vertebral trabecular bone. It is hypothesized that the unique topology of the vertebral trabecular structure can be used to extract reliable feature points that can be registered to produce higher resolution strain fields compared to traditional digital volume correlation (DVC) techniques. A validation study comparing Scale Invariant Feature Transform and Skeletonization approaches for feature registration and Thin Plate Spline interpolation and Meshless Methods approximation for strain calculation was conducted. Using an ideal 2% linearly increasing strain field, the Skeletonization with Meshless Method approach yielded the best performance, with an accuracy of -405µstrain and a detection limit of 1210µstrain, similar to standard DVC performance. A hybrid feature/DVC registration algorithm may further improve the ability to measure vertebral strain.