Abstract:
Automated or semiautomated segmentation of medical images descreases
interstudy variation, observer bias, and postprocessing time as well
as providing clinically-relevant quantitative data. In this paper we
present a new dynamic deformable modeling approach to 3D segmentation.
It utilizes recently developed dynamic remeshing techniques and curvature
estimation methods to produce high-quality meshes. The approach has been
implemented in an interactive environment that allows a user to specify
an initial model and identify key features in the data. These features
act as hard constraints that the model must not pass through as it deforms.
We have employed the method to perform semi-automatic segmentation of
heart structures from cine MRI data.