Turkish Journal of Pathology

Türk Patoloji Dergisi

Turkish Journal of Pathology

Turkish Journal of Pathology

2023, Vol 39, Num, 2     (Pages: 101-108)

Whole Slide Images in Artificial Intelligence Applications in Digital Pathology: Challenges and Pitfalls

Kayhan BASAK 1, Kutsev Bengisu OZYORUK 2, Derya DEMIR 3

1 University of Health Sciences, Kartal Dr. Lütfi Kırdar City Hospital, Department of Pathology, ISTANBUL, TURKEY
2 Bogazici University, Department of Biomedical Engineering, ISTANBUL, TURKEY
3 Ege University, Faculty of Medicine, Department of Pathology, IZMIR, TURKEY

DOI: 10.5146/tjpath.2023.01601
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The use of digitized data in pathology research is rapidly increasing. The whole slide image (WSI) is an indispensable part of the visual examination of slides in digital pathology and artificial intelligence applications; therefore, the acquisition of WSI with the highest quality is essential. Unlike the conventional routine of pathology, the digital conversion of tissue slides and the differences in its use pose difficulties for pathologists. We categorized these challenges into three groups: before, during, and after the WSI acquisition. The problems before WSI acquisition are usually related to the quality of the glass slide and reflect all existing problems in the analytical process in pathology laboratories. WSI acquisition problems are dependent on the device used to produce the final image file. They may be related to the parts of the device that create an optical image or the hardware and software that enable digitization. Post-WSI acquisition issues are related to the final image file itself, which is the final form of this data, or the software and hardware that will use this file. Because of the digital nature of the data, most of the difficulties are related to the capabilities of the hardware or software. Being aware of the challenges and pitfalls of using digital pathology and AI will make pathologists' integration to the new technologies easier in their daily practice or research.

Keywords : Whole slide images, Artificial intelligence, Digital pathology, Challenges