Surface Preserving Resampling of Labeled Images

Thanks to the development of microscopy techniques, the acquisition of temporal series of 3D images is becoming a standard for the study of evolving phenomena (e.g. developmental biology). In most cases, live samples are moving/growing during long-term imaging, therefore it is desirable to compensate for this global 3D motion for both a more comfortable visualization and analysis. It is implicitly assumed that the quantitative properties of the resampled series are similar (if not equal) to those of the original one. Among these properties, the surface measurement is quite important since it helps predicting cell behavior, fate, or to compute symmetry axis. In the present work, we demonstrated that surface estimation of segmented objects may not be preserved by the nearest neighbor interpolation, the usual technique to resampled label images, and proposed a novel interpolation technique, dedicated for multi-labeled images, that preserves the surface estimation.