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GTCreator: a flexible annotation tool for image-based datasets

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

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

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

References

  1. El-Regaily SA, Salem MA, Abdel Aziz MH, Roushdy MI (2018) Survey of computer aided detection systems for lung cancer in computed tomography. Curr Med Imaging Rev 14(1):3–18

    Article  Google Scholar 

  2. Gui L, Yang X (2018) Automatic renal lesion segmentation in ultrasound images based on saliency features, improved lbp, and an edge indicator under level set framework. Med Phys 45(1):223–235

    Article  Google Scholar 

  3. Sánchez FJ, Bernal J, Sánchez-Montes C, de Miguel CR, Fernández-Esparrach G (2017) Bright spot regions segmentation and classification for specular highlights detection in colonoscopy videos. Mach Vis Appl 28(8):917–936

    Article  Google Scholar 

  4. Mori Y, Kudo Se, Berzin TM, Misawa M, Takeda K (2017) Computer-aided diagnosis for colonoscopy. Endoscopy 49(08):813–819

    Article  Google Scholar 

  5. Bernal J, Tajkbaksh N, Snchez FJ, Matuszewski BJ, Chen H, Yu L, Angermann Q, Romain O, Rustad B, Balasingham I, Pogorelov K, Choi S, Debard Q, Maier-Hein L, Speidel S, Stoyanov D, Brandao P, Crdova H, Snchez-Montes C, Gurudu SR, Fernndez-Esparrach G, Dray X, Liang J, Histace A (2017) Comparative validation of polyp detection methods in video colonoscopy: results from the miccai 2015 endoscopic vision challenge. IEEE Trans Med Imaging 36(6):1231–1249

    Article  Google Scholar 

  6. Chen PJ, Lin MC, Lai MJ, Lin JC, Lu HHS, Tseng VS (2018) Accurate classification of diminutive colorectal polyps using computer-aided analysis. Gastroenterology 154(3):568–575

    Article  Google Scholar 

  7. Russell BC, Torralba A, Murphy KP, Freeman WT (2008) Labelme: a database and web-based tool for image annotation. Int J Comput Vis 77(1):157–173

    Article  Google Scholar 

  8. Dutta A, Gupta A, Zissermann A (2016) VGG image annotator (VIA). http://www.robots.ox.ac.uk/~vgg/software/via/. Accessed 21 Jan 2018

  9. Iakovidis D, Goudas T, Smailis C, Maglogiannis I (2014) Ratsnake: a versatile image annotation tool with application to computer-aided diagnosis. Sci World J 2014:1–12

    Article  Google Scholar 

  10. Liu D, Cao Y, Kim KH, Stanek S, Doungratanaex-Chai B, Lin K, Tavanapong W, Wong J, Oh J, De Groen PC (2007) Arthemis: annotation software in an integrated capturing and analysis system for colonoscopy. Comput Methods Programs Biomed 88(2):152–163

    Article  Google Scholar 

  11. Rubin DL, Rodriguez C, Shah P, Beaulieu C (2008) ipad: semantic annotation and markup of radiological images. In: AMIA annual symposium proceedings, vol 2008. American Medical Informatics Association, p 626

  12. Several authors (2013) Video image annotation tool. https://sourceforge.net/projects/via-tool/. Accessed 22 Jan 2018

  13. Abràmoff MD, Magalhães PJ, Ram SJ (2004) Image processing with imagej. Biophoton Int 11(7):36–42

    Google Scholar 

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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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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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  • DOI: https://doi.org/10.1007/s11548-018-1864-x

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