Table of Contents
Journal of Computational Medicine
Volume 2014 (2014), Article ID 542521, 11 pages
Research Article

Context-Based Separation of Cell Clusters for the Automatic Biocompatibility Testing of Implant Materials

Institute for Computer Science, Vision and Computational Intelligence, South Westphalia University of Applied Sciences, Frauenstuhlweg 31, 58644 Iserlohn, Germany

Received 30 September 2013; Revised 23 January 2014; Accepted 2 February 2014; Published 20 March 2014

Academic Editor: Daniel Kendoff

Copyright © 2014 S. Buhl et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents a new method to separate cells on microscopic surfaces joined together in cell clusters into individual cells. Important features of this method are that the remaining object geometry is preserved and few contour points are required for finding joints between neighboring cells. There are alternative methods such as morphological operations or the watershed transformation based on the inverse distance transformation but they have certain disadvantages compared to the method presented in this paper. The discussed method contains knowledge-based components in form of a decision function and exchangeable rules to avoid unwanted separations.