This paper focuses on the problem of contour extraction in medical images and shows that this segmentation task can be viewed as a tracking problem. The influence of the speckle noise and of the high nonlinearities is overcome by Monte Carlo methods. An efficient multiple model Monte Carlo algorithm for progressive contour growing (tracking) is developed, accounting for convex, non-circular forms of delineated contour areas. The driving idea of the proposed filter consists in the incorporation of different image intensity inside and outside the contour into the filter likelihood. A PDA procedure using the contour edge mag- nitude is applied to cope with the measurement origin uncertainty. The filter performance is studied by ex- tracting contours from a number of real and simulated ultrasound medical images and very good accuracy is achieved.