Abstract
It has been shown that it is possible to differentiate viable amniotic membrane towards osteogenic lineage, i.e. bony tissue. This process of mineralization may take several weeks and can show different manifestations per sample. The tissue can only be used, when the mineralization process is advanced in a certain degree. Therefore, a forecast of the development of mineralization would be helpful to save time and resources. This paper shows how a prediction on the development of mineralization can be made by using several image processing techniques, machine learning methods, and hybrid ensembles of machine learning algorithms.
The work described in this paper was done within the FIT-IT project number 835918 NanoDetect sponsored by the Austrian Research Promotion Agency (FFG).
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Notes
- 1.
HeuristicLab: http://dev.heuristiclab.com/.
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Obritzberger, L. et al. (2015). Prediction of Stem Cell Differentiation in Human Amniotic Membrane Images Using Machine Learning. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2015. EUROCAST 2015. Lecture Notes in Computer Science(), vol 9520. Springer, Cham. https://doi.org/10.1007/978-3-319-27340-2_40
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DOI: https://doi.org/10.1007/978-3-319-27340-2_40
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