Abstract
Statistical models of shape and appearance are powerful tools for medical image analysis. The shape models can capture the mean and variation in shape of a structure or set of structures across a population. They can be used to help interpret new images by finding the parameters which best match an instance of the model to the image. Two widely used methods for matching are the Active Shape Model and the Active Appearance Model. We describe the models and the matching algorithms, and give examples of their use.
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