Cell Tracking according to Biological Needs -- Strong Mitosis-aware Random-finite Sets Tracker with Aleatoric Uncertainty

arXiv:2403.15011v1 Announce Type: new
Abstract: Cell tracking and segmentation assist biologists in extracting insights from large-scale microscopy time-lapse data. Driven by local accuracy metrics, current tracking approaches often suffer from a lack of long-term consistency. To address this issue, we introduce an uncertainty estimation technique for neural tracking-by-regression frameworks and incorporate it into our novel extended Poisson multi-Bernoulli mixture tracker. Our uncertainty estimation identifies uncertain associations within high-performing tracking-by-regression methods using problem-specific test-time augmentations. Leveraging this uncertainty, along with a …

abstract accuracy arxiv cs.cv current data insights issue long-term metrics microscopy random scale segmentation tracking type uncertainty