This project will develop a neuron-tracking microscope system that utilizes built in knowledge of neuronal morphology to perform three-dimensional neuron tracing with minimal human assistance. It will be accomplished by integrating newly created expert system and computer vision software with a computer driven video light microscope. The software will be designed for an existing Zeiss - Sun 3/160C video imaging computer microscope system. The expert microscopy system (EMS) will acquire a depth sequence of images of the neuron and its neighborhood. The sequence will include all of the neuron's branching structure. The EMS will analyze the images, treating them just as the human would treat the ordinary visual images he obtains while tracing the same neuron. Human assistance will be called upon at the outset of data acquisition in order to guide the system to the neuron in question, and then later only if the system is incapable of making a reliable decision based upon its existing knowledge base. The system will produce 3-D neuronal maps containing all the structural data of interest. These will permit computer graphic reconstructions (including dynamic rotations) as well as numerical morphometric analyses. They will also permit spatial analyses of populations of neurons. The EMS is intended to be capable of performing at least as well as a trained human using the same knowledge base. The software will be designed to be device independent and therefore transportable to other imaging systems. It will also be applicable to the new high resolution scanning confocal microscopes. The architectural organization of the nervous system is highly complex, with one nerve cell making numerous interconnections with other cells. Presently, neuroscientists must mechanically trace the course of a neuron shown in microscopic images. The software to be developed will automatically perform this task, saving substantial man-hours. This capability will accelerate the acquisition of data to be analyzed for underlying patterns, leading to greater understanding of the relationship of structure to function.
