Medical image segmentation using a simulated charged fluid

Deformable models are important and popular techniques for extracting the shape of objects in medical images. We used the simulation of a physical system (a Charged Fluid) to guide the evolution of a propagating interface to segment objects in brain MR and CT images. The Charged Fluid was simulated as a system of charged particles that exert a repelling electric force upon each other. In our approach, the boundary of the segmenting object was determined by the image gradient, which was modeled as potential wells that stopped the propagating front. The simulation was evolved in two steps that were governed by Poisson's equation. One allowed the propagating interface of the Charged Fluid to deform into a new shape in response to the electric potential and the image potential. The other allowed Charged Fluid elements to flow along the propagating interface, which was treated as the surface of an isolated conductor, until an electrostatic equilibrium was achieved. The electric potential of the simulated system was rapidly computed from Poisson's equation by the aid of the Fast Fourier Transform. The procedure was repeated until the propagating front resided on the boundary of objects being segmented. This method was used to extract the contour of the brain surface for use in skull stripping applications.