DIGITAL PATHOLOGY
these fundamental elements will ensure that digital pathology evolves as a technological advancement that is reliable, scalable, and ultimately supports the future of patient care.
References 1 Bancroft JD, Gamble M. Theory and
practice of histological techniques. 8th edn. Philadelphia: Elsevier, 2019. doi:10.1016/ C2015-0-00143-5
2
Krupinski EA, Tillack AA, Richter L, et al. Eye-movement study and human performance using virtual microscopy. Arch Pathol Lab Med. 2006;130(8):1197-1203. doi:10.5858/2006-130-1197-ESAHPU
3 Schot AG. Elevating Microscopy Workflows: How ISO 8255-1 compliant coverslips enhance efficiency and precision. (Schot AG; 2023)
www.schot.com/en-au/expertise/ applications/glass-for-automated- coverslipper
4 Hobson A, Finn R. How slide choice influences background staining, digital scan efficiency, and data burden. (StatLab; 2026)
www.statlab.com/statcontent/kt-slides- background-staining/
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Litjens G, Kooi T, Bejnordi BE, et al. A survey on deep learning in medical image analysis. Med Image Anal. 2017;42:60-88. doi:10.1016/
j.media.2017.07.005
6 Tizhoosh HR, Pantanowitz L. Artificial Intelligence and Digital Pathology:
Challenges and Opportunities. J Pathol Inform. 2018;9:38. doi:10.4103/
jpi.jpi_53_18
7 Hodder A. AI-Driven Artifact Detection Improves Diagnostic Accuracy in Digital Pathology Systems. (Future Medicine; 2024)
www.futuremedicine.com/articles/ ai-driven-artifact-detection-improves- diagnostic-accuracy-in-digital-pathology- systems
8 Pantanowitz L, Sinard JH, Henricks WH, et al. Validating whole slide imaging for diagnostic purposes in pathology: guideline from the College of American Pathologists Pathology and Laboratory Quality Center. Arch Pathol Lab Med. 2013;137(12):1710-1722. doi:10.5858/ arpa.2013-0093-CP
Rachel Finn MBA HTL (ASCP)CM is the Product Marketing Specialist at StatLab Medical Products, where she merges her deep expertise in pathology with a passion for education and innovation. With over 12 years of hands-on experience as a histotechnologist, laboratory supervisor, and product support specialist, Rachel brings authoritative knowledge in H&E techniques, special stains, and immunohistochemistry. In her current role, she leads the development of engaging, informative product content and contributes to StatLab’s R&D Innovation Council, helping to shape new product development through her practical insights and strategic perspective.
www.statlab.com
Studies evaluating AI in pathology have shown that variability in staining, slide
PPi
preparation, and imaging conditions can significantly impact AI model accuracy and transferability across facilities
June 2026
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