Prostate segmentation in echographic images: A variational approach using deformable super-ellipse and rayleigh distribution

We present a simple, robust and computationally efficient method for the semi-automatic segmentation of the prostate in TRUS (Transrectal Ultrasound) image. The method relies on a variational formulation based on a deformable super- ellipse and a region energy based on the assumption of a Rayleigh distribution. Instead of using the classical level-set approach, we directly insert the implicit representation of a deformable super-ellipse into the energy to minimize. This yields a super-ellipse evolution able to accurately segment prostate and surrounding tissues while handling boundary gaps on the contour.