Deformable models and the analysis of medical images.
Deformable models are a popular and vigorously researched model-based approach to computer-assisted medical image analysis. The widely recognized efficacy of deformable models stem from their ability to segment, match and track images of anatomic structures by exploiting (bottom-up) constraints derived from the image data together with (top-down) a priori knowledge about the location, size and shape of structures of interest. Deformable models are capable of accommodating the often significant variability of biological structures over time and across different individuals. Furthermore, they support highly intuitive interaction mechanisms that allow medical scientists and practitioners to bring their expertise to bear on the model-based image interpretation task as necessary. In this paper we will review deformable models and present some recent developments in the methodology, including topologically adaptable deformable models, an approach that permits segmentation and reconstruction of topologically complex anatomical structures.
Terzopoulos
D
D
Department of Computer Science, University of Toronto, ON, Canada. dt tim@cs.toronto.edu
McInerney
T
T
D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods