Andreopoulos A., Statistical Models of Appearance for Functional Analysis of
Cardiac MRI. M.Sc. Thesis
York University, May 2005.
We present a framework for the analysis of cardiac MRI using Statistical Models of
Appearance. This thesis makes three major contributions. The first contribution
involves the introduction of a new algorithm for fitting 3-D Active Appearance
Models on cardiac MRI, using the inverse compositional image alignment algorithm.
We observe a 60-fold increase in fitting speed and an accuracy that is on
par with Gauss-Newton optimization. The second contribution involves an investigation
of the use of wavelets in hierarchical Active Shape Models, as a potential
way of making them more expressively powerful. The third contribution involves
an investigation of the use of adaptive filtering for high quality resampling of 4-D
cardiac MR images. We show the high quality results that are derived by the
use of adaptive filtering, and describe the ways in which it could improve the
automated analysis of medical images. [PDF]