ML Anthology

CTMC: Cell Tracking with Mitosis Detection Dataset Challenge

Samreen Anjum, Danna Gurari
CVPRW 2020 pp. 4228-4237
doi:10.1109/CVPRW50498.2020.00499 /cvprw/2020/anjum2020cvprw-ctmc/

Abstract

While significant developments have been made in cell tracking algorithms, current datasets are still limited in size and diversity, especially for data-hungry generalized deep learning models. We introduce a new larger and more diverse cell tracking dataset in terms of number of sequences, length of sequences, and cell lines, accompanied with a public evaluation server and leaderboard to accelerate progress on this new challenging dataset. Our benchmarking of four top performing tracking algorithms highlights new challenges and opportunities to improve the state-of-the-art in cell tracking.

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Cite

Text

Anjum and Gurari. "CTMC: Cell Tracking with Mitosis Detection Dataset Challenge." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2020. doi:10.1109/CVPRW50498.2020.00499

Markdown

[Anjum and Gurari. "CTMC: Cell Tracking with Mitosis Detection Dataset Challenge." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2020.](https://mlanthology.org/cvprw/2020/anjum2020cvprw-ctmc/) doi:10.1109/CVPRW50498.2020.00499

BibTeX

@inproceedings{anjum2020cvprw-ctmc,
  title     = {{CTMC: Cell Tracking with Mitosis Detection Dataset Challenge}},
  author    = {Anjum, Samreen and Gurari, Danna},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2020},
  pages     = {4228-4237},
  doi       = {10.1109/CVPRW50498.2020.00499},
  url       = {https://mlanthology.org/cvprw/2020/anjum2020cvprw-ctmc/}
}