Finite elements allow smoothness to be enforced on the measurement of the image-dependent term in active contours. This improves the stability of the solution, with less computational cost than is incurred by increasing the number of elements. Performance is best when the size of the element matches the scale of the image detail sought.

Uejormable models of elastic structures have been proposed for use in image analysis. The models are based on a minimum energy principle which incorporates both image information and "high level" knowledge of the structures involved. This paper reports a further development of the Finite Element Method (FEM) for use in active contour models. It is shown that parabolic and cubic Finite Elements provide a versatile technique for implementing deformable models. The method is demonstrated on MR and x-ray images of brain sections.

Deformable models of elastic structures have been proposed for use in image analysis. Previous work has used a variational approach, based on the EulerLagrange theory. In this paper an alternative mathematical treatment is introduced, based on a direct minimisation of the underlying energy integral using the Finite Element Method. The method is outlined and demonstrated, and its principal advantages for modelbased image interpretation are explained.