Smoothing algorithms allow one to reduce artifacts from mesh generation, but often degrade accuracy. The method described in the paper "Context- aware mesh smoothing for biomedical applications" identifies staircase artifacts which result from image inhomogeneities and binary segmentation in medical image data for subsequent removal by adaptive mesh smoothing. Thus, context-aware smoothing enables to adaptively smooth artifact areas, while non-artifact features can be preserved. This is a implementation of this method in Cpp with Python bindings.