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Using high-resolution image capture devices in the neurosciences makes it possible to gain a huge number of new insights into the structure-functional relations of the central nervous system and his dysfunctions occuring in the context of neurodegenerative diseases.
Nowadays latest image capture devices (e.g. confocal laser scan microscopes) acquire high-resolution, n-dimensional image stacks. After mounting single image data stacks into a whole image data stack the neuro-scientist is able to visualize and analyze therefore larger, coherent areas receiving the highest possible cellular resolution.
As for the scientist, the main problem consists in accepting a compromise if Imaging Software is limited in terms of supply, the management, the visualization and the analysis of large, n-dimensional image datasets.
Our aim is to develop an Imaging software which offers an innovative and unique solution for the unsolved problems with handling of almost unlimited multidimensional image datasets. Therefore we developed the arivs browser in cooperation with Leibniz Institute of Neurobiology, Magdeburg.
(see also Research Group Project "Virtual Brain" of BMBF)
In Leibniz Institute for Neurobiology, Magdeburg it was intendend to apply confocal laser scan microscopes in order to get very high resolution images of living neurons.
With the arivis Browser it was for the first time possible, to visualize smallest structures within a complete neuron.
Thus, the animation above shows a time series recording which is documenting the movements of dentritical spines.
With the help of the arivis Browser the total image of the neutron was set up. After an alignment of the single images, this small extract was exported from the image stack.
With the aid of the Look-up-tables (LUT), which are integrated into the arivis Browser, it is easily possible to attain very complex changes in the visualization of the image data in terms of color. In the following, these changes can be used by other visualization or analysis modules which facilitates a classification of different objects and the evaluation of the image data.