engleski

Semi-Automatic Cell Correspondence Analysis Using Iterative Point Cloud Registration

In the field of biophysics, deformation of in- vitro model tissues is an experimental technique to explore the response of tissue to a mechanical stimulus. However, automated registration before and after deformation is an ongoing obstacle for measuring the tissue response on the cellular level. Here, we propose to use an iterative point cloud registration (IPCR) method, for this problem. We apply the registration method on point clouds representing the cellular centers of mass, which are evaluated with aWatershed based segmentation of phase-contrast images of living tissue, acquired before and after deformation. Preliminary evaluation of this method on three data sets shows high accuracy, with 82% - 92% correctly registered cells, which outperforms coherent point drift (CPD). Hence, we propose the application of the IPCR method on the problem of cell correspondence analysis.

Deformation ; Image segmentation ; Surface measurement

Funding text Acknowledgement. This work has partly been supported by the European Research Council to ASS (ERC StG 2013-337283, MEMBRANESACT), by the German Research Foundation to ASS and DD (RTG 1962), and by the Emerging Field Initiative of the FAU Erlangen- Nürnberg: Big-Thera to AM, ASS and DD. SBN 978-3-658-25325-7 ; ISBN 978-3-658-25326-4 (e-book)