GTCreator: a flexible annotation tool for image-based datasets

Abstract

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.

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Notes

  1. 1.

    A demo version of GTCreator is available at http://www.cvc.uab.es/CVCColon/.

  2. 2.

    Available at https://giana.grand-challenge.org/.

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Funding

This work has been funded by Spanish Government through iVENDIS (DPI2015-65286-R), DeepMTL (TIN2016-79717-R) and HISINVIA(PI17/00894) projects, Catalan government through SGR-2017-1669 , SGR-2017-653 and CERCA programme, Région Île de France through SATT funding “iPolyp” (Project 184). A. Histace and J. Bernal acknowledge the Institute of Advanced Studies from UCP (Invited Prof. Position grant) as well as Initiative Paris Seine through which the position was obtained in the context of “iPolyp”. M. Masana acknowledges 2017FIB-00218 grant of Generalitat de Catalunya. We also acknowledge the generous GPU support from NVIDIA.

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Correspondence to Jorge Bernal.

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The authors declare that they have no conflict of interest.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all individual participants included in the study.

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Bernal, J., Histace, A., Masana, M. et al. GTCreator: a flexible annotation tool for image-based datasets. Int J CARS 14, 191–201 (2019). https://doi.org/10.1007/s11548-018-1864-x

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Keywords

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