Recent advances in digital image processing hardware providing very high pixel resolutions can be exploited to solve problems in correlating high magnification feature analysis with specimen macrostructure. In neuroscience, for instance, analyses such as neuron counting which are performed at high magnification often need to be correlated with the overall structure of the specimen. Typically these procedures involve tediously moving between very low and very high power objectives. Once at high power, the positional knowledge of the objects of interest can be difficult to maintain.

By integrating high resolution image capture with precise microscope automation, a digital composite image of the specimen can be created. Such composite images show the researcher a high resolution “map” of the specimen, facilitating the analysis of both macro- and microstructure characteristics from a single view.