Motion analysis of nonrigid objects by active contour models using multiscale images

This paper considers the approach to dynamic image processing, which is one of the important problems in the future medical image processing. The tracking of the object and the analysis of the motion are discussed for the dynamic images of a nonrigid object with smooth shape, motion and deformation, which is the case in most medical images. This approach is based on an active contour model defined by an energy function in terms of both intra- and interframe constraints for the contour of the object. The contour of the target object is extracted and tracked by minimizing the energy function using multiscale dynamic programming and the motion is analyzed. The dynamic programming in multiscale proposed in this paper is to adjust the search neighborhood of the dynamic programming according to the scale. The coarse or fine neighborhood is defined for the coarse and fine scales, respectively, and the energy is minimized starting from the coarse scale and shifting to the fine scale. By this scheme, a large motion an deformation of the object can be handled. The proposed motion tracking method has been applied successfully to the dynamic image in the `behavioral analysis of a slug aiming at the analysis of the neural mechanism of learning and memory formation in slugs,' as well as to dynamic echocardiographic images. In the first application, the positive maximum of the curvature along the contour is extracted in the motion analysis as a characteristic point invariant to the deformation of the object. Then the shift of that point is traced. By this approach, the rough motion of the object can be estimated.