The registration of retinal images is required to facilitate the study of the optic nerve head and the retina. The method we propose combines the use of mutual information as the similarity measure and simulated annealing as the search technique. It is robust toward large transformations between the images and significant changes in light intensity. By using a pyramid sampling approach combined with simulated reannealing we find that registration can be achieved to predetermined precision, subject to choice of interpolation and the constraint of time. The algorithm was tested on 49 pairs of stereo images and 48 pairs of temporal images with success.

This article describes the statistical methods used in quantitative and mixed methods articles between 2006 and 2010 in five gifted education research journals. Results indicate that the most commonly used statistical methods are means (85.9% of articles), standard deviations (77.8%), Pearson's r (47.8%), χ 2 (32.2%), ANOVA (30.7%), t tests (30.0%), and MANOVA (23.0%). Approximately half (53.3%) of the articles included reliability reports for the data at hand; Cronbach's alpha was the most commonly reported measure of reliability (41.5%). Some discussions of best statistical practice and implications for the field of gifted education are included.

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