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Bildverarbeitung für die Medizin 2013

Part of the series Informatik aktuell pp 116-121

Date:

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

  • Nico ScherfAffiliated withInstitute for Medical Informatics and Biometry, TU Dresden Email author 
  • , Michael KunzeAffiliated withInstitute for Medical Informatics, Statistics and Epidemiology, University of Leipzig
  • , Konstantin ThierbachAffiliated withInstitute for Medical Informatics and Biometry, TU Dresden
  • , Thomas ZerjatkeAffiliated withInstitute for Medical Informatics and Biometry, TU Dresden
  • , Patryk BurekAffiliated withInstitute for Medical Informatics, Statistics and Epidemiology, University of Leipzig
  • , Heinrich HerreAffiliated withInstitute for Medical Informatics, Statistics and Epidemiology, University of Leipzig
  • , Ingmar GlaucheAffiliated withInstitute for Medical Informatics and Biometry, TU Dresden
  • , Ingo RoederAffiliated withInstitute for Medical Informatics and Biometry, TU Dresden

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Zusammenfassung

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.