Multiple Hypothesis Tracking With Integrated Cell Division Detection
| Autor: | Karl Rohr, Christian Ritter, D. Schacherer |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0303 health sciences
Cell division business.industry Computer science Probabilistic logic Pattern recognition Tracking (particle physics) Synthetic data 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Data association Multiple hypothesis tracking Medical imaging Artificial intelligence business Image resolution 030304 developmental biology |
| Zdroj: | ISBI |
| Popis: | Automatic tracking of proliferating cells in microscopy images is important to elucidate biological processes. We have developed a new probabilistic approach for cell tracking which is based on Multiple Hypothesis Tracking and integrates cell division detection. Our method uses information from multiple frames and formulates data association with cell division detection as graph-theoretical maximum weighted independent set problem. We evaluated our approach using synthetic data as well as data from the Cell Tracking Challenge. It turned out that our approach generally improves the results for cell tracking and cell division detection compared to previous methods. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|