A DIGITAL BRAIN ATLAS FOR SURGICAL PLANNING, MODEL-DRIVEN SEGMENTATION, AND TEACHING

We developed a three-dimensional (3D) digitized atlas of the human bra in to visualize spatially complex structures. It was designed for use with magnetic resonance (MR) imaging data sets. Thus far, we have used this atlas for surgical planning, model-driven segmentation, and teac hing. We used a combination of automated and supervised segmentation m ethods to define regions of interest based on neuroanatomical knowledg e. We also used 3D surface rendering techniques to create a brain atla s that would allow us to visualize complex 3D brain structures. We fur ther linked this information to script files in order to preserve both spatial information and neuroanatomical knowledge. We present here th e application of the atlas for visualization-ih surgical planning for model-driven segmentation and for the teaching of neuroanatomy. This d igitized human brain has the potential to provide important reference information for the planning of surgical procedures. It can also serve as a powerful teaching tool, since spatial relationships among neuroa natomical structures can be more readily envisioned when the user is a ble to view and rotate the structures in 3D space. Moreover, each elem ent of the brain atlas is associated with a name tag, displayed by a u ser-controlled pointer. The atlas holds a major promise as a template for model-driven segmentation. Using this technique, many regions of i nterest can be characterized simultaneously on new brain images.