title: An active particle-based tracking framework for 2D and 3D time-lapse microscopy images.
abstract: The process required to track cellular structures is a key task in the study of cell migration. This allows the accurate estimation of motility indicators that help in the understanding of mechanisms behind various biological processes. This paper reports a particle-based fully automatic tracking framework that is able to quantify the motility of living cells in time-lapse images. Contrary to the standard tracking methods based on predefined motion models, in this paper we reformulate the tracking mechanism as a data driven optimization process to remove its reliance on a priory motion models. The proposed method has been evaluated using 2D and 3D deconvolved epifluorescent in-vivo image sequences that describe the development of the quail embryo.
authors.affiliation: Centre for Image Processing and Analysis, Dublin City University, Glasnevin, Dublin 9, Ireland. julius.hossain@dcu.ie
authors.forename: M Julius
authors.initials: MJ
authors.lastname: Hossain
authors.forename: Paul F
authors.initials: PF
authors.lastname: Whelan
authors.forename: Andras
authors.initials: A
authors.lastname: Czirok
authors.forename: Ovidiu
authors.initials: O
authors.lastname: Ghita
mesh_terms: D000465:Algorithms; D000818:Animals; D002465:Cell Movement; D001330:Electronic Data Processing; D005456:Fluorescent Dyes / Q000494:pharmacology; D049452:Green Fluorescent Proteins / Q000378:metabolism; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional / Q000379:methods; D008853:Microscopy / Q000379:methods*; D008856:Microscopy, Fluorescence / Q000379:methods; D015233:Models, Statistical; D008962:Models, Theoretical; D009038:Motion; D011784:Quail; D012815:Signal Processing, Computer-Assisted
chemical_list: D005456:Fluorescent Dyes; D049452:Green Fluorescent Proteins