English

The TUM LapChole dataset for the M2CAI 2016 workflow challenge

Computer Vision and Pattern Recognition 2017-09-01 v2
Authors: Ralf Stauder , Daniel Ostler , Michael Kranzfelder , Sebastian Koller , Hubertus Feußner , Nassir Navab
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Abstract

In this technical report we present our collected dataset of laparoscopic cholecystectomies (LapChole). Laparoscopic videos of a total of 20 surgeries were recorded and annotated with surgical phase labels, of which 15 were randomly pre-determined as training data, while the remaining 5 videos are selected as test data. This dataset was later included as part of the M2CAI 2016 workflow detection challenge during MICCAI 2016 in Athens.

Cite

@article{arxiv.1610.09278,
  title  = {The TUM LapChole dataset for the M2CAI 2016 workflow challenge},
  author = {Ralf Stauder and Daniel Ostler and Michael Kranzfelder and Sebastian Koller and Hubertus Feußner and Nassir Navab},
  journal= {arXiv preprint arXiv:1610.09278},
  year   = {2017}
}

Comments

5 pages, 2 figures, preliminary reference for published dataset (until larger comparison study of workshop organizers is published)

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