Multiple Hypothesis Tracking With Integrated Cell Division Detection

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 mult...

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Bibliographic Details
Published in2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI) pp. 165 - 168
Main Authors Schacherer, D., Ritter, C., Rohr, K.
Format Conference Proceeding
LanguageEnglish
Published IEEE 13.04.2021
Subjects
Biological processes
Biomedical imaging
Cell tracking
Cells (biology)
Image resolution
Image sequences
Microscopy
Microscopy images
Multiple hypothesis tracking
Probabilistic logic
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Summary: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.
ISSN:1945-8452
DOI:10.1109/ISBI48211.2021.9434153