Assisting the Machine Paradigms for Human-Machine Interaction in Single Cell Tracking

Conference paper
Part of the Informatik aktuell book series (INFORMAT)


Single cell tracking emerged as one of the fundamental experimental techniques over the past years in basic life science research. Though a large number of automated tracking methods has been introduced, they are still lacking the accuracy to reliably track complete cellular genealogies over many generations. Manual tracking on the other hand is tedious and slow. Semi-automated approaches to cell tracking are a good compromise to obtain comprehensive information in feasible amounts of time. In this work, we investigate the efficacy of different interaction paradigms for manual correction and processing of precomputed tracking results and present a respective tool that implements those strategies.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Institute for Medical Informatics and BiometryTU DresdenDresdenDeutschland
  2. 2.Institute for Medical Informatics, Statistics and EpidemiologyUniversity of LeipzigLeipzigDeutschland

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