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Accurate image segmentation continues to be one of the biggest challenges in medical image analysis.  Simple, low-level vision techniques have had limited success in this domain because of the visual complexity of medical images.  This paper presents a 3-D shape model that uses prior knowledge of an object's structure to guide the search for its boundaries.  The shape model has been incorporated into SCANNER, an interactive software package for image segmentation.  We describe a graphical user interface that was developed for finding the surface of the brain and explain how the 3-D model assists with the segmentation process.  Preliminary experiments show that with this shape-based approach, a low-resolution boundary for a surface can be found with two-thirds less work for the user than with a comparable manual method. 

Kewywords: interactive 3-D image segmentation, constraint-based shape models, knowledge-based medical imaging