2D Image-based reconstruction of shape deformation of biological structures using a level-set representation

This paper copes with the reconstruction of accretionary growth sequence from images of bi2 ological structures depicting concentric ring patterns. Accretionary growth shapes are modeled as the level-sets of a potential function. Given an image of a biological structure, the recon4 struction of the sequence of growth shapes is stated as a variational issue derived from geometric criteria. This variational setting exploits image-based information, in terms of the orientation 6 field of relevant image structures, which leads to an original advection term. The resolution of this variational issue is discussed. Experiments on synthetic and real data are reported to 8 validate the proposed approach.