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Semi-Automatic Cell Correspondence Analysis Using Iterative Point Cloud Registration

Chen, Shuqing; Gehrer, Simone; Kaliman, Sara; Ravikumar, Nishant; Becit, Abdurrahman; Aliee, Maryam; Dudziak, Diana; Merkel, Rudolf; Smith, Ana Sunčana; Maier, Andreas K. (2019) Semi-Automatic Cell Correspondence Analysis Using Iterative Point Cloud Registration. Bildverarbeitung für die Medizin. Informatik aktuell., 2019 . pp. 116-121. ISSN 1431-472X

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Abstract

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.

Item Type: Article
Uncontrolled Keywords: Deformation ; Image segmentation ; Surface measurement
Subjects: NATURAL SCIENCES > Mathematics
NATURAL SCIENCES > Mathematics > Applied Mathematics and Mathematical Modeling
NATURAL SCIENCES > Physics > Condensed Matter Physics
Divisions: Division of Physical Chemistry
Projects:
Project titleProject leaderProject codeProject type
Biological Membranes in Action: A Unified Approachto Complexation, Scaffolding and Active Transport-MEMBRANESACTUNSPECIFIED337283EK
Depositing User: Ana Sunčana Smith
Date Deposited: 24 Mar 2020 10:57
Last Modified: 24 Mar 2020 10:57
URI: http://fulir.irb.hr/id/eprint/5373
DOI: 10.1007/978-3-658-25326-4_26

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