In this work we present the first algorithm for restoring consistency between curve networks on non-parallel cross-sections. Our method addresses a critical but overlooked challenge in the reconstruction process from cross-sections that stems from the fact that cross-sectional slices are often generated independently of one another, such as in interactive volume segmentation. As a result, the curve networks on two non-parallel slices may disagree where the slices intersect, which makes these cross- sections an invalid input for surfacing. We propose a method that takes as input an arbitrary number of non-parallel slices, each partitioned into two or more labels by a curve network, and outputs a modified set of curve networks on these slices that are guaranteed to be consistent. We formulate the task of restoring consistency while preserving the shape of input curves as a constrained optimization problem, and we propose an effective solution framework. We demonstrate our method on a data-set of complex multi-labeled input cross-sections. Our technique efficiently produces consistent curve networks even in the presence of large errors.