GTCreator: a flexible annotation tool for image-based datasets

Jorge Bernal, Aymeric Histace, Marc Masana, Quentin Angermann, Cristina Sánchez-Montes, Cristina Rodríguez de Miguel, Maroua Hammami, Ana García-Rodríguez, Henry Córdova, Olivier Romain, Gloria Fernández-Esparrach, Xavier Dray, F. Javier Sánchez

Research output: Contribution to journalArticleResearch

20 Citations (Scopus)


© 2018, CARS. Purpose:: Methodology evaluation for decision support systems for health is a time-consuming task. To assess performance of polyp detection methods in colonoscopy videos, clinicians have to deal with the annotation of thousands of images. Current existing tools could be improved in terms of flexibility and ease of use. Methods:: We introduce GTCreator, a flexible annotation tool for providing image and text annotations to image-based datasets. It keeps the main basic functionalities of other similar tools while extending other capabilities such as allowing multiple annotators to work simultaneously on the same task or enhanced dataset browsing and easy annotation transfer aiming to speed up annotation processes in large datasets. Results:: The comparison with other similar tools shows that GTCreator allows to obtain fast and precise annotation of image datasets, being the only one which offers full annotation editing and browsing capabilites. Conclusion:: Our proposed annotation tool has been proven to be efficient for large image dataset annotation, as well as showing potential of use in other stages of method evaluation such as experimental setup or results analysis.
Original languageEnglish
Pages (from-to)191-201
JournalInternational journal of computer assisted radiology and surgery
Publication statusPublished - 1 Feb 2019


  • Annotation tool
  • Benchmark
  • Colonoscopy
  • Evaluation
  • Validation framework


Dive into the research topics of 'GTCreator: a flexible annotation tool for image-based datasets'. Together they form a unique fingerprint.

Cite this