Image analysis of self-organized multicellular patterns : multicellular pattern formation on compliant elastomer surfaces as model system
- Analysis of multicellular patterns is required to understand tissue organizational processes. By using a multi-scale object oriented image processing method, the spatial information of cells can be extracted automatically. Instead of manual segmentation or indirect measurements, such as general distribution of contrast or flow, the orientation and distribution of individual cells is extracted for quantitative analysis. Relevant objects are identified by feature queries and no low-level knowledge of image processing is required.
| Author of HS Reutlingen | Thies, Christian; Khachaturyan, Galina; Kemkemer, Ralf |
|---|---|
| URN: | urn:nbn:de:bsz:rt2-opus4-12348 |
| DOI: | https://doi.org/10.1515/cdbme-2016-0116 |
| eISSN: | 2364-5504 |
| Erschienen in: | Current directions in biomedical engineering |
| Publisher: | De Gruyter |
| Place of publication: | Berlin |
| Document Type: | Journal article |
| Language: | English |
| Publication year: | 2016 |
| Tag: | cell segmentation; image analysis; object extraction; phase contrast micrographs; spatial information; tissue organization |
| Volume: | 2 |
| Issue: | 1 |
| Page Number: | 5 |
| First Page: | 523 |
| Last Page: | 527 |
| DDC classes: | 570 Biowissenschaften, Biologie |
| Open access?: | Ja |
| Licence (German): |  Creative Commons - Namensnennung, nicht kommerziell, keine Bearbeitung |
