Variational Level-Set Reconstruction of Accretionary Morphogenesis from Images

Abstract

This paper copes with the reconstruction of accretionary morphogenesis within a given observation plane from an image depicting successive (typically seasonal or daily) growth structures. Modeling accretionary growth shapes as the level-sets of a potential function, a variational framework is derived from geometric criteria. It resorts to minimizing an energy functional involving two terms: a regularization term and a data-driven term which constrain the evolution of the shapes with respect to a growth orientation field. Experiments carried out on real data (e.g., fish otoliths) validate the proposed approach, which opens new research directions for information extraction and decoding from biological archives.

Modeling cellular deformations using the level set formalism

“…The Level Set Method (LSM) can be used to overcome these difficulties [ 19 ]. LSM is a numerical technique for tracking interfaces and shapes which has been widely used in various fields including computer graphics [ 20 ], image processing [ 21 ], computational fluid dynamics [ 22 ] and material science [ 23 ].…”