In this paper, we propose a new paradigm to reconstruct 3D volume from histology slices guided by NURBS spline-based feature curves. Histology slices are first scanned into computer as a sequence of image files with a histology film scanner. An initial 3D alignment of the images is obtained through the histological similarity matching between neighboring slices. Further optimization is achieved by applying optimal affine transformation to each slice according to feature curve smoothing. Considering the intrinsic smoothness of the physical features, we compute the transformation to refine the selected features based on NURBS splines. Consequently, volume reconstruction is further optimized. We also present new evaluation methods to prove that our reconstruction scheme can achieve a high accuracy.