ArticleJournal of pathology informatics2023
Whole slide imaging (WSI) scanner differences influence optical and computed properties of digitized prostate cancer histology.
Article in Journal of pathology informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed.
- Comparison and image analysis of different file formats on whole-slide images for colorectal and non-small cell lung carcinomas.Journal of pathology informatics · 2026Article
- Comparative analysis of whole-slide scanner tissue detection algorithms: Implications for scan area, scan time, and file size in high-volume digital pathology workflows.Journal of pathology informatics · 2026Article
- Development of an automated artificial intelligence-based tool for reticulin fibrosis assessment in bone marrow biopsies.Virchows Archiv : an international journal of pathology · 2026Article
- The PAR dataset: Prostate biopsy whole slide images from an underrepresented Middle Eastern population.Scientific data · 2026Article
- Overcoming Variability in RNAscope Image Analysis: A HALO-Based Approach.Methods in molecular biology (Clifton, N.J.) · 2026Article
- [Research progress and future prospects for artificial intelligence in the diagnosis and treatment of fatty liver disease].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2025Review
- Digital slide scanning at scale: Comparison of whole slide imaging devices in a clinical setting.Journal of pathology informatics · 2025Article
- Article
- Using artificial intelligence to prioritize pathology samples: report of a test drive.Virchows Archiv : an international journal of pathology · 2025Article
- The Role of Artificial Intelligence in the Evaluation of Prostate Pathology.Pathology international · 2025Review
- Corr-A-Net: Interpretable Attention-Based Correlated Feature Learning framework for predicting of HER2 Score in Breast Cancer from H&E Images.medRxiv : the preprint server for health sciences · 2025Article
- Review
- An international study of stain variability in histopathology using qualitative and quantitative analysis.Journal of pathology informatics · 2025Article
- VS-FPM: Large-Format, Label-Free Virtual Histopathology Microscopy.BME frontiers · 2025Article
- The tumour histopathology "glossary" for AI developers.PLoS computational biology · 2025Review
- Computational pathology: A survey review and the way forward.Journal of pathology informatics · 2024Review
- Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Purpose: Digital pathology is becoming an increasingly popular area of advancement in both research and clinically. Pathologists are now able to manage and interpret slides digitally, as well as collaborate with external pathologists with digital copies of slides. Differences in slide scanners include variation in resolution, image contrast, and optical properties, which may influence downstream image processing. This study tested the hypothesis that varying slide scanners would result in differences in computed pathomic features on prostate cancer whole mount slides. Design: This study collected 192 unique tissue slides from 30 patients following prostatectomy. Tissue samples were paraffin-embedded, stained for hematoxylin and eosin (H&E), and digitized using 3 different scanning microscopes at the highest available magnification rate, for a total of 3 digitized slides per tissue slide. These scanners included a ( Results: Each mean color channel intensity (i.e., Red, Green, Blue) differed between slide scanners (all Conclusion: This study demonstrates that both optical and computed properties of digitized histological samples are impacted by slide scanner differences. Future research is warranted to better understand which scanner properties influence the tissue segmentation process and to develop harmonization techniques for comparing data across multiple slide scanners.
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Registered trials
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