Symmetry-Based Mitosis Detection in Time-Lapse Microscopy

Topaz Gilad, Mark Anthony Bray, Anne E. Carpenter, Tammy Riklin Raviv

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

11 Scopus citations


Providing a general framework for mitosis detection is challenging. The variability of the visual traits and temporal features which classify the event of cell division is huge due to the numerous cell types, perturbations, imaging techniques and protocols used in microscopy imaging analysis studies. The commonly used machine learning techniques are based on the extraction of comprehensive sets of discriminative features from labeled examples and therefore do not apply to general cases as they are restricted to trained datasets. We present a robust mitotic event detection algorithm that accommodates the difficulty of the different cell appearances and dynamics. Addressing symmetrical cell divisions, we consider the anaphase stage, immediately after the DNA material divides, at which the two daughter cells are approximately identical. Having detected pairs of candidate daughter cells, based on their association to potential mother cells, we look for the respective symmetry axes. Mitotic event is detected based on the calculated measure of symmetry of each candidate pair of cells. Promising mitosis detection results for four different time-lapse microscopy datasets were obtained.

Original languageEnglish
Title of host publication2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015
PublisherInstitute of Electrical and Electronics Engineers
Number of pages4
ISBN (Electronic)9781479923748
StatePublished - 2015
Event12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 - Brooklyn, United States
Duration: 16 Apr 201519 Apr 2015

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452


Conference12th IEEE International Symposium on Biomedical Imaging, ISBI 2015
Country/TerritoryUnited States


  • High-throughput images
  • Mitosis detection
  • Symmetry
  • Time-lapse Microscopy

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging


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