Kostelec, P. D., Carlin, L. M. and Glocker, B. (2015) Learning to Detect and Track Cells for Quantitative Analysis of Time-Lapse Microscopic Image Sequences. In: 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), New York, NY, USA, 16-19 Apr 2015, pp. 1544-1547. ISBN 9781479923748 (doi: 10.1109/ISBI.2015.7164172)
Full text not currently available from Enlighten.
Abstract
Studying the behaviour of cells using time-lapse microscopic imaging requires automated processing pipelines that enable quantitative analysis of a large number of cells. We propose a pipeline based on state-of-the-art methods for background motion compensation, cell detection, and tracking which are integrated into a novel semi-automated, learning based analysis tool. Motion compensation is performed by employing an efficient nonlinear registration method based on powerful discrete graph optimisation. Robust detection and tracking of cells is based on classifier learning which only requires a small number of manual annotations. Cell motion trajectories are generated using a recent global data association method and linear programming. Our approach is robust to the presence of significant motion and imaging artifacts. Promising results are presented on different sets of in-vivo fluorescent microscopic image sequences.
| Item Type: | Conference Proceedings |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Carlin, Dr Leo |
| Authors: | Kostelec, P. D., Carlin, L. M., and Glocker, B. |
| College/School: | College of Medical Veterinary and Life Sciences > School of Cancer Sciences |
| Journal Name: | 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI) |
| ISSN: | 1945-7928 |
| ISBN: | 9781479923748 |
| Published Online: | 23 July 2015 |
University Staff: Request a correction | Enlighten Editors: Update this record
Deposit and Record Details
Deposit and Record Details