Recent development of advanced quantitative methods to fully analyze the intrinsic information contained in images, have begun to unearth the rich treasures they contain and to exploit their full scientific, educational and/or biomedical value. structural alterations found in the brains of patients with Alzheimer's disease. The second project concerns the three-dimensional reconstruction of the internal membrane system of neurons involved in the regulation of intracellular calcium. The final project involves the use of tomographic reconstruction techniques to visualize components of the nervous systems in thick sections imaged with the aid of intermediate high voltage electron microscopy. parameter sensitivity directions to determine identifiability for a capillary exchange model. The method is based on a vector definition of model sensitivity to parameter values. The results are images which provide immediate recognition of the identifiability of the parameters over wide ranges. processing and analysis. We propose a smoothing algorithm which preserves edges and thus fine structures common in biomedical images. The algorithm is based on averaging over an independently generated mask at each pixel. The mask generation takes into account local image information and conforms to tissue boundaries. Comparison of the proposed algorithm with other common smoothing techniques favors our algorithm. with the psychological properties in central vision, however, apparent movement in peripheral vision have not been clearly understood. This study focuses on the properties of the perception of apparent movement between central and peripheral vision. improve upon existing image reconstruction techniques in Electrical Impedance Tomography. The dynamics of the network are surprisingly simple and retain the possibility of analog implementation. Compared to the algorithms currently used in EIT, the proposed method differs in its emphasis on relaxation processing and rigorous mathematical support.