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International Conference on Pattern Recognition

ICPR 2021: Pattern Recognition. ICPR International Workshops and Challenges pp 263–274Cite as

The EndoTect 2020 Challenge: Evaluation and Comparison of Classification, Segmentation and Inference Time for Endoscopy

Part of the Lecture Notes in Computer Science book series (LNIP,volume 12668)

Abstract

The EndoTect challenge at the International Conference on Pattern Recognition 2020 aims to motivate the development of algorithms that aid medical experts in finding anomalies that commonly occur in the gastrointestinal tract. Using HyperKvasir, a large dataset containing images taken from several endoscopies, the participants competed in three tasks. Each task focuses on a specific requirement for making it useful in a real-world medical scenario. The tasks are (i) high classification performance in terms of prediction accuracy, (ii) efficient classification measured by the number of images classified per second, and (iii) pixel-level segmentation of specific anomalies. Hopefully, this can motivate different computer science researchers to help benchmark a crucial component of a future computer-aided diagnosis system, which in turn, could potentially save human lives.

Keywords

  • GI endoscopy
  • Anomaly detection
  • Segmentation
  • Accuracy
  • Efficient processing
  • Challenge

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Fig. 1.
Fig. 2.

Notes

  1. 1.

    https://github.com/simula/hyper-kvasir.

  2. 2.

    https://github.com/simula/endotect-2020-submission-evaluation.

  3. 3.

    https://pjreddie.com/darknet/tiny-darknet/.

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Authors and Affiliations

  1. SimulaMet, Oslo, Norway

    Steven A. Hicks, Debesh Jha, Vajira Thambawita, Pål Halvorsen, Hugo L. Hammer & Michael A. Riegler

  2. Oslo Metropolitan University, Oslo, Norway

    Steven A. Hicks, Vajira Thambawita, Pål Halvorsen & Hugo L. Hammer

  3. UIT The Arctic University of Norway, Tromsø, Norway

    Debesh Jha

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Correspondence to Steven A. Hicks .

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Editors and Affiliations

  1. Dipartimento di Ingegneria dell’Informazione, University of Firenze, Firenze, Italy

    Prof. Alberto Del Bimbo

  2. Dipartimento di Ingegneria “Enzo Ferrari”, Università di Modena e Reggio Emilia, Modena, Italy

    Prof. Rita Cucchiara

  3. Department of Computer Science, Boston University, Boston, MA, USA

    Prof. Stan Sclaroff

  4. Dipartimento di Matematica e Informatica, University of Catania, Catania, Italy

    Dr. Giovanni Maria Farinella

  5. Cloud & AI, JD.COM, Beijing, China

    Tao Mei

  6. Dipartimento di Ingegneria dell’Informazione, University of Firenze, Firenze, Italy

    Prof. Dr. Marco Bertini

  7. Computational Sciences Department, National Institute of Astrophysics, Optics and Electronics (INAOE), Tonantzintla,, Puebla, Mexico

    Hugo Jair Escalante

  8. Dipartimento di Ingegneria “Enzo Ferrari”, Università di Modena e Reggio Emilia, Modena, Italy

    Dr. Roberto Vezzani

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Hicks, S.A., Jha, D., Thambawita, V., Halvorsen, P., Hammer, H.L., Riegler, M.A. (2021). The EndoTect 2020 Challenge: Evaluation and Comparison of Classification, Segmentation and Inference Time for Endoscopy. In: , et al. Pattern Recognition. ICPR International Workshops and Challenges. ICPR 2021. Lecture Notes in Computer Science(), vol 12668. Springer, Cham. https://doi.org/10.1007/978-3-030-68793-9_18

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