Joint cell segmentation and tracking using cell proposals

Saad Ullah Akram, Juho Kannala, Lauri Eklund, Janne Heikkilä

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

15 Citations (Scopus)


Time-lapse microscopy imaging has advanced rapidly in last few decades and is producing large volume of data in cell and developmental biology. This has increased the importance of automated analyses, which depend heavily on cell segmentation and tracking as these are the initial stages when computing most biologically important cell properties. In this paper, we propose a novel joint cell segmentation and tracking method for fluorescence microscopy sequences, which generates a large set of cell proposals, creates a graph representing different cell events and then iteratively finds the most probable path within this graph providing cell segmentations and tracks. We evaluate our method on three datasets from ISBI Cell Tracking Challenge and show that our greedy nonoptimal joint solution results in improved performance compared with state of the art methods.

Original languageEnglish
Title of host publication2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings
PublisherIEEE Computer Society
Number of pages5
ISBN (Electronic)9781479923502
ISBN (Print)978-1-4799-2349-6
Publication statusPublished - 15 Jun 2016
MoE publication typeA4 Article in a conference publication
EventIEEE International Symposium on Biomedical Imaging - Prague, Czech Republic
Duration: 13 Apr 201616 Apr 2016
Conference number: 13

Publication series

ISSN (Print)1945-7928
ISSN (Electronic)1945-7936


ConferenceIEEE International Symposium on Biomedical Imaging
Abbreviated titleISBI
CountryCzech Republic


  • cell proposals
  • cell segmentation
  • cell tracking
  • joint segmentation and tracking

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