Moral Lineage Tracing

Abstract

Lineage tracing, the tracking of living cells as they move and divide, is a central problem in biological image analysis. Solutions, called lineage forests, are key to understanding how the structure of multicellular organisms emerges. We propose an integer linear program (ILP) whose feasible solutions define, for every image in a sequence, a decomposition into cells (segmentation) and, across images, a lineage forest of cells (tracing). In this ILP, path-cut inequalities enforce the morality of lineages, i.e., the constraint that cells do not merge. To find feasible solutions of this NP-hard problem, with certified bounds to the global optimum, we define efficient separation procedures and apply these as part of a branch-and-cut algorithm. To show the effectiveness of this approach, we analyze feasible solutions for real microscopy data in terms of bounds and run-time, and by their weighted edit distance to lineage forests traced by humans.

Cite

Text

Jug et al. "Moral Lineage Tracing." Conference on Computer Vision and Pattern Recognition, 2016. doi:10.1109/CVPR.2016.638

Markdown

[Jug et al. "Moral Lineage Tracing." Conference on Computer Vision and Pattern Recognition, 2016.](https://mlanthology.org/cvpr/2016/jug2016cvpr-moral/) doi:10.1109/CVPR.2016.638

BibTeX

@inproceedings{jug2016cvpr-moral,
  title     = {{Moral Lineage Tracing}},
  author    = {Jug, Florian and Levinkov, Evgeny and Blasse, Corinna and Myers, Eugene W. and Andres, Bjoern},
  booktitle = {Conference on Computer Vision and Pattern Recognition},
  year      = {2016},
  doi       = {10.1109/CVPR.2016.638},
  url       = {https://mlanthology.org/cvpr/2016/jug2016cvpr-moral/}
}