Parameter estimation for a deformable template model

  • Authors:
  • Merrilee Hurn;Ingelin Steinsland;Håvard Rue

  • Affiliations:
  • Mathematical Sciences, University of Bath, Bath BA2 7AY, UK. M.A.Hurn@bath.ac.uk;Department of Mathematical Sciences, NTNU, Norway. ingelins@stat.ntnu.no;Department of Mathematical Sciences, NTNU, Norway. havard.rue@stat.ntnu.no

  • Venue:
  • Statistics and Computing
  • Year:
  • 2001

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Abstract

In recent years, a number of statistical models have been proposed for the purposes of high-level image analysis tasks such as object recognition. However, in general, these models remain hard to use in practice, partly as a result of their complexity, partly through lack of software. In this paper we concentrate on a particular deformable template model which has proved potentially useful for locating and labelling cells in microscope slides Rue and Hurn (1999). This model requires the specification of a number of rather non-intuitive parameters which control the shape variability of the deformed templates. Our goal is to arrange the estimation of these parameters in such a way that the microscope user's expertise is exploited to provide the necessary training data graphically by identifying a number of cells displayed on a computer screen, but that no additional statistical input is required. In this paper we use maximum likelihood estimation incorporating the error structure in the generation of our training data.