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SHR Neuro Krebs Kardio Lipid Stoffw Microb

Jahn, SW; Plass, M; Moinfar, F.
Digital Pathology: Advantages, Limitations and Emerging Perspectives.
J Clin Med. 2020; 9(11): Doi: 10.3390/jcm9113697 [OPEN ACCESS]
Web of Science PubMed PUBMED Central FullText FullText_MUG


Führende Autor*innen der Med Uni Graz
Jahn Stephan
Co-Autor*innen der Med Uni Graz
Moinfar Farid
Plass Markus

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Digital pathology is on the verge of becoming a mainstream option for routine diagnostics. Faster whole slide image scanning has paved the way for this development, but implementation on a large scale is challenging on technical, logistical, and financial levels. Comparative studies have published reassuring data on safety and feasibility, but implementation experiences highlight the need for training and the knowledge of pitfalls. Up to half of the pathologists are reluctant to sign out reports on only digital slides and are concerned about reporting without the tool that has represented their profession since its beginning. Guidelines by international pathology organizations aim to safeguard histology in the digital realm, from image acquisition over the setup of work-stations to long-term image archiving, but must be considered a starting point only. Cost-efficiency analyses and occupational health issues need to be addressed comprehensively. Image analysis is blended into the traditional work-flow, and the approval of artificial intelligence for routine diagnostics starts to challenge human evaluation as the gold standard. Here we discuss experiences from past digital pathology implementations, future possibilities through the addition of artificial intelligence, technical and occupational health challenges, and possible changes to the pathologist's profession.

Find related publications in this database (Keywords)
digital pathology
machine learning
artificial intelligence
whole slide imaging
occupational health
computer vision syndrome
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