FEASIBILITY OF A NEXT GENERATION COMPUTER ENVIRONMENT FOR ASSISTING 3D RECONSTRUCTION AND ANALYSIS OF NEURAL ANATOMY

THE QUESTIONS OF DEVELOPMENT, FUNCTION, AND PLASTICITY REPRESENT MAJOR UNSOLVED PROBLEMS IN MODERN BIOLOGY. THESE QUESTIONS REQUIRE SOPHISTICATED 3D SERIAL RECONSTRUCTIONS FROM ELECTRON MICROGRAPHS OF ARRAYS OF INDIVIDUALLY IDENTIFIED NEURONS. HOWEVER, USING PRESENTLY AVAILABLE TECHNOLOGY, RECONSTRUCTIONS ARE VERY DIFFICULT, HUMAN-INTENSIVE PROCESSES, AND RESULTS ARE INADEQUATE. ADVANCED DECISION SYSTEMS PROPOSES TO DETERMINE THE FEASIBILITY AND INITIAL DESIGN OF A RECONSTRUCTION ENVIRONMENT THAT PERFORMS SEMI-AUTOMATED PROCESSING OF NEURON NETWORKS, EACH WITH COMPLEX 3D SHAPE AND CONTACTS, AND THAT INTERACTIVELY AIDS THE NEURO-BIOLOGIST IN UNDERSTANDING THE 3D STRUCTURES. THE PROPOSED TECHNICAL APPROACH IS TO USE TECHNIQUES IN MODEL-BASED COMPUTER VISION TO: ELICIT AND CHARACTERIZE AN EXPERT'S PERCEPTUAL AND FUNCTIONAL 3D MODELS OF NEURAL BODIES AND THEIR SPATIAL RELATIONSHIPS; DETERMINE THE FEASIBILITY OF REPRESENTING THESE MODELS IN A COMPUTER ENVIRONMENT; USE THESE MODELS TO GUIDE 2D IMAGE STRUCTURE EXTRACTION AND 3D VOLUMETRIC RECONSTRUCTION;AND SPECIFY THE HUMAN MACHINE INTERFACE REQUIREMENTS TO MEANINGFULLY AID IN PERFORMING NEUROBIOLOGICAL RESEARCH. THE DEVELOPMENT OF EXPERT PERCEPTUAL MODELS OF NEURAL ANATOMY IS UNIQUE TO NEUROBIOLOGY; IT CANNOT BE ACHIEVED SOLELY THROUGH ADVANCES IN COMPUTER VISION. (GENERIC COMPUTER SCIENCE ISSUES WILL NOT BE ADDRESSED).