title: Ct3d: tracking microglia motility in 3D using a novel cosegmentation approach.
abstract: BACKGROUND
  Cell tracking is an important method to quantitatively analyze time-lapse microscopy data. While numerous methods and tools exist for tracking cells in 2D time-lapse images, only few and very application-specific tracking tools are available for 3D time-lapse images, which is of high relevance in immunoimaging, in particular for studying the motility of microglia in vivo.
  
  
  RESULTS
  We introduce a novel algorithm for tracking cells in 3D time-lapse microscopy data, based on computing cosegmentations between component trees representing individual time frames using the so-called tree-assignments. For the first time, our method allows to track microglia in three dimensional confocal time-lapse microscopy images. We also evaluate our method on synthetically generated data, demonstrating that our algorithm is robust even in the presence of different types of inhomogeneous background noise.
  
  
  BACKGROUND
  Our algorithm is implemented in the ct3d package, which is available under http://www.picb.ac.cn/patterns/Software/ct3d; supplementary videos are available from http://www.picb.ac.cn/patterns/Supplements/ct3d.
authors.affiliation: Department of Biophysics, Institute of Neuroscience, Shanghai Institutes for Biological Sciences, 200031 Shanghai, China.
authors.forename: Hang
authors.initials: H
authors.lastname: Xiao
authors.forename: Ying
authors.initials: Y
authors.lastname: Li
authors.forename: Jiulin
authors.initials: J
authors.lastname: Du
authors.forename: Axel
authors.initials: A
authors.lastname: Mosig
mesh_terms: D000465:Algorithms; D000818:Animals; D002465:Cell Movement; D058948:Cell Tracking / Q000379:methods*; D019295:Computational Biology / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D017628:Microglia / Q000166:cytology*; D018613:Microscopy, Confocal; D012984:Software; D015027:Zebrafish