Abstract
Series of microscope recordings of cells, labeled for many different molecules, contain important biological information. The correct interpretation of those coupled multi-images, however, is not directly possible. This paper introduces a procedure for the analysis of higher-level combinatorical receptor patterns in the cellular immune system, which were obtained using the fluorescence multi-epitope-imaging microscopy. The cell recognition and the classification algorithm with an artificial neural network is described.
This work was supported by the DFG/BMBF grant (Innovationskolleg 15/A1).
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© 1996 Springer-Verlag Berlin Heidelberg
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St. Schünemann, Rethfeldt, C., Müller, F., Agha-Amiri, K., Michaelis, B., Schubert, W. (1996). Analysis of coupled multi-image information in microscopy. In: Höhne, K.H., Kikinis, R. (eds) Visualization in Biomedical Computing. VBC 1996. Lecture Notes in Computer Science, vol 1131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0046949
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DOI: https://doi.org/10.1007/BFb0046949
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