An Image Generator Platform to Improve Cell Tracking Algorithms

Pedro Canelas, Leonardo Martins, André Mora, Andre S Ribeiro, José Fonseca

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Several major advances in Cell and Molecular Biology have been made possible by recent advances in livecell microscopy imaging. To support these efforts, automated image analysis methods such as cell segmentation and tracking during a time-series analysis are needed. To this aim, one important step is the validation of such image processing methods. Ideally, the "ground truth" should be known, which is possible only by manually labelling images or in artificially produced images. To simulate artificial images, we have developed a platform for simulating biologically inspired objects, which generates bodies with various morphologies and kinetics and, that can aggregate to form clusters. Using this platform, we tested and compared four tracking algorithms: Simple Nearest-Neighbour (NN), NN with Morphology and two DBSCAN-based methods. We show that Simple NN works well for small object velocities, while the others perform better on higher velocities and when clustering occurs. Our new platform for generating new benchmark images to test image analysis algorithms is openly available at (http://griduni.uninova.pt/Clustergen/ClusterGen-v1.0.zip).
Original languageEnglish
Title of host publicationProceedings of the 6th International Conference on Simulation and Modeling Methodologies, Technologies and Applications
PublisherSCITEPRESS - Science and Technology Publications
Pages44-55
Number of pages12
ISBN (Print)978-989-758-199-1
DOIs
Publication statusPublished - 2016
Event6th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Lisbon, Portugal
Duration: 29 Jul 201631 Jul 2016

Conference

Conference6th International Conference on Simulation and Modeling Methodologies, Technologies and Applications
Abbreviated titleSIMULTECH 2016
CountryPortugal
CityLisbon
Period29/07/1631/07/16

Keywords

  • cell tracking
  • Cluster Tracking
  • Microscopy
  • Synthetic Time-lapse Image Simulation

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