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A whole-slide image grading benchmark and tissue classification for cervical cancer precursor lesions with inter-observer variability

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Abstract

The cervical cancer developing from the precancerous lesions caused by the human papillomavirus (HPV) has been one of the preventable cancers with the help of periodic screening. Cervical intraepithelial neoplasia (CIN) and squamous intraepithelial lesion (SIL) are two types of grading conventions widely accepted by pathologists. On the other hand, inter-observer variability is an important issue for final diagnosis. In this paper, a whole-slide image grading benchmark for cervical cancer precursor lesions is created and the “Uterine Cervical Cancer Database” introduced in this article is the first publicly available cervical tissue microscopy image dataset. In addition, a morphological feature representing the angle between the basal membrane (BM) and the major axis of each nucleus in the tissue is proposed. The presence of papillae of the cervical epithelium and overlapping cell problems are also discussed. Besides that, the inter-observer variability is also evaluated by thorough comparisons among decisions of pathologists, as well as the final diagnosis.

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Acknowledgements

The authors also would like to thank Argenit Company and Istanbul Medipol University Hospital for providing and annotating the whole-slide histopathological images of cervical cancer precursor lesions image dataset. The authors would like to thank the reviewers for all useful and instructive comments on our manuscript.

Funding

This work is in part funded by ITU BAP MAB-2020-42314 project and also supported by the Scientific Research Projects Coordination Department, Yildiz Technical University, under Project 2014-04-01-KAP01.

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Authors and Affiliations

  1. Department of Computer Engineering, Dicle University, Diyarbakır, 21280, Turkey

    Abdulkadir Albayrak

  2. Selahaddin Eyyubi State Hospital, Diyarbakır, 21100, Turkey

    Asli Unlu Akhan

  3. Department of Biomedical Engineering, Istanbul Medeniyet University, Istanbul, 34700, Turkey

    Nurullah Calik

  4. Informatics Institute, Istanbul Technical University, Istanbul, 34469, Turkey

    Abdulkerim Capar, Behcet Ugur Toreyin & Lutfiye Durak-Ata

  5. Department of Computer Engineering, Yildiz Technical University (YTU), 34220, Istanbul, Turkey

    Gokhan Bilgin

  6. Signal and Image Processing Laboratory (SIMPLAB), Yildiz Technical University, Istanbul, 34220, Turkey

    Abdulkadir Albayrak & Gokhan Bilgin

  7. Department of Pathology, Istanbul Medipol University Hospital, Istanbul, 34214, Turkey

    Bahar Muezzinoglu

  8. Pathology Center of Memorial Healthcare Group, Istanbul, 34385, Turkey

    Ilknur Turkmen

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  1. Abdulkadir Albayrak
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Correspondence to Gokhan Bilgin.

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Albayrak, A., Akhan, A.U., Calik, N. et al. A whole-slide image grading benchmark and tissue classification for cervical cancer precursor lesions with inter-observer variability. Med Biol Eng Comput 59, 1545–1561 (2021). https://doi.org/10.1007/s11517-021-02388-w

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  • DOI: https://doi.org/10.1007/s11517-021-02388-w

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