The development of new medicines against virus infections like the Marburg virus disease requires an accurate knowledge of the respective pathogens. Conventionally, this process is very time expensive. In cooperation with the Virology of the Philipps-University in Marburg an automatic tracking algorithm for subviral particles in fluorescence image sequences was developed and programmed. To expand the benefit for the pharmaceutical researchers, also the trackevaluations need to be widely automated. In this work, a new parameterizing-method facing the fractal dimensions of spline interpolated subviral particle tracks is presented and tested with simulated and real data. The results reveal a good potential to classify tracks and, thus, types of subviral particles in infected cells.
© 2018 the author(s), published by Walter de Gruyter Berlin/Boston
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.