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

Abdulkadir Albayrak, Asli Unlu Akhan, Nurullah Calik, Abdulkerim Capar, Gokhan Bilgin*, Behcet Ugur Toreyin, Bahar Muezzinoglu, Ilknur Turkmen, Lutfiye Durak-Ata

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

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. [Figure not available: see fulltext.].

Original languageEnglish
Pages (from-to)1545-1561
Number of pages17
JournalMedical and Biological Engineering and Computing
Volume59
Issue number7-8
DOIs
Publication statusPublished - Aug 2021

Bibliographical note

Publisher Copyright:
© 2021, International Federation for Medical and Biological Engineering.

Keywords

  • Cervical cancer
  • Cervical intraepithelial neoplasia (CIN)
  • Digital pathology
  • Histopathological images
  • Human papillomavirus
  • Inter-observer variability
  • Morphological features
  • Squamous intraepithelial lesion (SIL)
  • Whole-slide imaging

Fingerprint

Dive into the research topics of 'A whole-slide image grading benchmark and tissue classification for cervical cancer precursor lesions with inter-observer variability'. Together they form a unique fingerprint.

Cite this