Abstract
This paper suggests a high-level continuous image model for planar star-shaped objects. Under this model, a planar object is a stochastic deformation of a star-shaped template. The residual process, describing the difference between the radius-vector function of the template and the object, is allowed to be non-stationary. Stationarity is obtained by a time change. A parametric model for the residual process is suggested and straightforward parameter estimation techniques are developed. The deformable template model makes it possible to detect pathologies as demonstrated by an analysis of a data set of cell nuclei from a benign and a malignant tumour, using stochastic deformations of ellipses.
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