# Tracking-Assisted Segmentation of Biological Cells

arXiv: https://arxiv.org/abs/1910.08735 · HTML: https://mlsanity.com/paper/1910.08735/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Oct 2019.

## Built on by (most cited first, 2 of 2)

- [Cell Tracking according to Biological Needs -- Strong Mitosis-aware Multi-Hypothesis Tracker with Aleatoric Uncertainty](https://mlsanity.com/paper/2403.15011/) (2024)
- [Cell Tracking-by-detection using Elliptical Bounding Boxes](https://mlsanity.com/paper/2310.04895/) (2023)

## Abstract (arXiv)

U-Net and its variants have been demonstrated to work sufficiently well in biological cell tracking and segmentation. However, these methods still suffer in the presence of complex processes such as collision of cells, mitosis and apoptosis. In this paper, we augment U-Net with Siamese matching-based tracking and propose to track individual nuclei over time. By modelling the behavioural pattern of the cells, we achieve improved segmentation and tracking performances through a re-segmentation procedure. Our preliminary investigations on the Fluo-N2DH-SIM+ and Fluo-N2DH-GOWT1 datasets demonstrate that absolute improvements of up to 3.8 % and 3.4% can be obtained in segmentation and tracking accuracy, respectively.