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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.

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.

To test the hypothesis that the median eminence microvasculature has a direct regulatory role in the hormonal communication between the brain and the pituitary gland, it is necessary to determine whether the physical means for such control (e.g. smooth muscle sphincters strategically located in the capillary plexus) actually exists. Our approach is to search for such structures in transmission electron micrographs of thin serial sections of the median eminence. The complexity of these images and the anticipated need to include large numbers of them in the study led us to consider computer reconstruction for this problem. We report here the successful three-dimensional reconstruction of capillary modules using digital image processing techniques for capillary feature detection/extraction, for construction of montages (mosaics) of overlapping images of the same section, and for automatic image registration by two independent methods without the use of fiducial marks. These tasks have been performed manually in nearly all the published neurobiological reconstructions; here they are performed by programs using only the mathematical properties of the images. Methods like those described here provide the only practical means for executing large scale reconstructions and gaining significant new information about the regulation of blood flow in this region of the brain.