Three dimensional point clouds acquired by range scanners often do not represent the environment precisely due to noise and errors in the acquisition process. These latter systematical errors manifest as deformations of different kinds in the 3D range image. This paper presents a novel approach to correct deformations by an analysis of the structures present in the environment and correcting them by non-rigid transformations. The resulting algorithms are used for creating high-accuracy 3D indoor maps.