Computed detection and quantitative morphometry of Alzheimer senile plaques.

Senile plaques (SP) are the most characteristic neuropathologic lesions of Alzheimer's disease (AD) and studies of plaque cortical distribution, density, and morphology may lead to new information about the origin and pathogenesis of this disease. We have developed an automated computer image analysis program to detect SP (including diffuse and mature forms) and to measure SP size, shape, and fractional area or load in digital micrographs of silver-stained tissue sections. The plaques are detected with adaptive thresholding, requiring no user interaction. Measures of SP size, morphology, and load are readily calculated from the pixel values in the detected SP features. These measurements are achieved accurately and exhaustively, and this method offers an alternative to manual SP counting. We demonstrate its application to 4 cases spanning the full range of the severity of the disease.

Computed three-dimensional reconstruction of median-eminence capillary modules: image alignment and correlation.

Image alignment is an absolute requirement for three-dimensional (3-D) reconstruction from serial sections, and Fourier correlation is the most powerful way to compute alignments. The rotational and translational components of misalignment can be corrected by an iterative correlation procedure, but for images having significant differences, alignment can fail with a likelihood proportional to the extent of the differences. We found that translational correction was determined much more reliably when low-pass filters were applied to the product transforms from which the correlations were calculated. Rotational corrections based on polar analyses of the auto-correlations of the images instead of on the images directly contributed to more accurate alignments. These methods were used to generate 3-D reconstructions of brain capillary modules from serial-section mosaics of digitized transmission electron micrographs.

Computed alignment of dissimilar images for three-dimensional reconstructions.

Three-dimensional reconstructions from serial section images require the accurate registration of those images. Image correlation is the most powerful computed alignment method and its performance on identical images, or parts thereof, has been thoroughly studied. Correlation alignments of complex, dissimilar images can fail, however, with a likelihood proportional to the magnitude of the differences. We report that alignments can be computed more reliably and more accurately (higher-valued correlation coefficients) by the combined use of lowpass-filtered product transforms (from which the correlation functions are formed), autocorrelation correction of rotational misalignment, and covariance correction of translation misalignment. A simple rule is proposed for the lowpass filter cutoff radius depending on measures of the images' differences. These methods are demonstrated with a reconstruction of a capillary loop in the median eminence of the hypothalamus.

Digital image reconstruction for the study of brain structure and function.

Functional activity of brain can be defined as the change in physiological activity that accompanies change in behavior. Although the precise relationship between such coupled activity is still being explored, autoradiographic methods for measuring brain blood flow, metabolism and receptor ligand densities have advanced to the point where it is possible to survey the entire brain of an animal for such changes. These developments offer the opportunity for studying brain as a whole--that is, for surveying the entire brain to identify the sites where changes in blood flow, metabolism or receptor chemistry occur with a particular behavior. The development of computer-based image analysis systems offer the possibility for visualizing such holistic brain function. We identified 4 steps which must be accomplished in developing a three-dimensional (3D) display for studying brain function. This paper describes the development and implementation of procedures for these 4 steps. Sectioning and digitizing representative tissue (e.g. autoradiograms, histology, histochemistry) with an adequate sampling frequency. Alignment and reconstruction of the components which make up the whole brain so that the original shape and orientation prior to sectioning is maintained. Projection and surface generation of a 3D model where the shading of the surface is mathematically dependent on the location of light source(s) and the viewer. Localization and quantification of planar cuts through the 3D model. Density data which reference the original autoradiograms are displayed along the exposed surface of the designated plane. The final presentation of data once these 4 steps are completed allows for the identification and visualization of changes in functional activity within the whole brain.