The long term aim of this project is to take emerging methods from computer graphics and extend state of the art in data collection, modeling, analysis and visualization of three-dimensional brain structures. The intent is to develop new algorithms and create a set of modular and re-usable tools for collect and interacting with multivalued anatomic information, as well as developing tools that aid in dissemination of this information. By developing new types of computation, the intent is to ultimately enable new types of diagnostic procedures and approaches for use by brain researchers and health practitioners. There are five related research areas in this project: 1) continued development of """"""""goal-based"""""""" data acquisition methods, 2) elucidation of microstructure from diffusion tensor data, 3) multivalued tissue classification algorithms, 4) semi-immersive visualization algorithms and interaction methods for display and data acquisition on a """"""""Responsive Workbench"""""""" and 5) new types of multivalued visualization methods, such as """"""""painterly"""""""" visualization. The project involves magnetic resonance micro-imaging, and two-photon and confocal microscopy. Using high resolution anatomical data from the Atlas Project and MRI Core and optical data from the Connectivity Project, tissues will be classified and visualized through their chemical composition and microstructure. The algorithms and an annotated subsets of the visualized data will be disseminated through publications and via the web.
