Adaptive level set image segmentation using the Mumford and Shah functional

This paper proposes an adaptive 2-phase level set image segmentation algorithm to improve the original level set-based piecewise constant Mumford-Shah model. With the introduction of a multiplicative gain field, the model is adaptive to intensity inhomogeneity, thus tending to obtain the actual boundaries of the objects, as well as a property-seeking and -driven classification algorithm.