Medical imagery, in particular three-dimensional imagery, provides highly accurate and informative insight into internal anatomical structure and function. While such data is becoming readily available for the clinician, very few tools have been developed to properly exploit the structural and geometric information inherent in the images. A key problem in medical image analysis is registration--the process of aligning datasets to the same coordinate frame. Accurate and automated image registration facilitates powerful solutions for such applications as surgical guidance, disease diagnosis, and treatment monitoring. A hierarchical 3D surface-based optimization approach is proposed to address these registration problems. The goals are to register same-subject imagery taken over time in a wide range of situations ranging from rigid to deformable tissues and to evaluate registration accuracy and reliability. Resultant prototype registration systems have been applied to image-guided surgery..