Multiphase Systems for Medical Image Region Classification.

Variational methods for region classification have shown very promising results in medical image analysis. The Chan-Vese model is one of the most popular methods, but its numerical resolution is slow and it has serious drawbacks for most multiphase applications. In this work, we extend the link, stablished by Chambolle, between the two classes binary Chan-Vese model and the Rudin-Osher-Fatemi (ROF) model to a multiphase four classes minimal partition problem. We solve the ROF image restoration model and then we threshold the image by means of a genetic algorithm. This strategy allows for a more efficient algorithm due to the fact that only one well posed elliptic problem is solved instead of solving the coupled parabolic equations arising in the original multiphase Chan-Vese model. [ABSTRACT FROM AUTHOR]