On-line Tracking of Cells and Their Lineage from Time Lapse Video Data
© 2018 IEEE. In this paper, we propose an algorithm for tracking cells that also provides lineage information. Our approach incorporates cell spawning into the random finite set dynamic model of the cell population, which allows the Bayes multi-object filter to capture information on the cells ances...
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| Format: | Conference Paper |
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IEEE
2018
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| Online Access: | http://purl.org/au-research/grants/arc/DP160104662 http://hdl.handle.net/20.500.11937/73834 |
| _version_ | 1848763110737838080 |
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| author | Dat Nguyen, T. Kim, Du Yong |
| author_facet | Dat Nguyen, T. Kim, Du Yong |
| author_sort | Dat Nguyen, T. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © 2018 IEEE. In this paper, we propose an algorithm for tracking cells that also provides lineage information. Our approach incorporates cell spawning into the random finite set dynamic model of the cell population, which allows the Bayes multi-object filter to capture information on the cells ancestries. A generalized Labeled Multi-Bernoulli (GLMB) filter (with cell spawning model) is applied to track the cells using detections extracted from time lapse video data. Numerical results on a set of stems cells demonstrate the capability of the proposed solution to track the time-varying number of cells as well as their ancestries. |
| first_indexed | 2025-11-14T10:58:15Z |
| format | Conference Paper |
| id | curtin-20.500.11937-73834 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:58:15Z |
| publishDate | 2018 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-738342022-10-27T06:24:08Z On-line Tracking of Cells and Their Lineage from Time Lapse Video Data Dat Nguyen, T. Kim, Du Yong © 2018 IEEE. In this paper, we propose an algorithm for tracking cells that also provides lineage information. Our approach incorporates cell spawning into the random finite set dynamic model of the cell population, which allows the Bayes multi-object filter to capture information on the cells ancestries. A generalized Labeled Multi-Bernoulli (GLMB) filter (with cell spawning model) is applied to track the cells using detections extracted from time lapse video data. Numerical results on a set of stems cells demonstrate the capability of the proposed solution to track the time-varying number of cells as well as their ancestries. 2018 Conference Paper http://hdl.handle.net/20.500.11937/73834 10.1109/ICCAIS.2018.8570546 http://purl.org/au-research/grants/arc/DP160104662 IEEE restricted |
| spellingShingle | Dat Nguyen, T. Kim, Du Yong On-line Tracking of Cells and Their Lineage from Time Lapse Video Data |
| title | On-line Tracking of Cells and Their Lineage from Time Lapse Video Data |
| title_full | On-line Tracking of Cells and Their Lineage from Time Lapse Video Data |
| title_fullStr | On-line Tracking of Cells and Their Lineage from Time Lapse Video Data |
| title_full_unstemmed | On-line Tracking of Cells and Their Lineage from Time Lapse Video Data |
| title_short | On-line Tracking of Cells and Their Lineage from Time Lapse Video Data |
| title_sort | on-line tracking of cells and their lineage from time lapse video data |
| url | http://purl.org/au-research/grants/arc/DP160104662 http://hdl.handle.net/20.500.11937/73834 |