ArticleJournal of pathology informatics2016
A quantitative approach to evaluate image quality of whole slide imaging scanners.
Article in Journal of pathology informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Agentic systems in computational pathology: architectures, evidence, and translational challenges.Journal of translational medicine · 2026Review
- Development of an automated artificial intelligence-based tool for reticulin fibrosis assessment in bone marrow biopsies.Virchows Archiv : an international journal of pathology · 2026Article
- Equipping computational pathology systems with artifact processing pipelines: a showcase for computation and performance trade-offs.BMC medical informatics and decision making · 2024Article
- Article
- Preparing Data for Artificial Intelligence in Pathology with Clinical-Grade Performance.Diagnostics (Basel, Switzerland) · 2023Review
- Histopathological Images Analysis and Predictive Modeling Implemented in Digital Pathology-Current Affairs and Perspectives.Diagnostics (Basel, Switzerland) · 2023Review
- Predicting gastric cancer outcome from resected lymph node histopathology images using deep learning.Nature communications · 2021Article
- Developing image analysis pipelines of whole-slide images: Pre- and post-processing.Journal of clinical and translational science · 2020Review
- Quantitative pixel intensity- and color-based image analysis on minimally compressed files: implications for whole-slide imaging.Histochemistry and cell biology · 2019Article
- Digital pathology and artificial intelligence.The Lancet. Oncology · 2019Review
- HistoQC: An Open-Source Quality Control Tool for Digital Pathology Slides.JCO clinical cancer informatics · 2019Article
- Stable and discriminating features are predictive of cancer presence and Gleason grade in radical prostatectomy specimens: a multi-site study.Scientific reports · 2018Article
- Constant Quest for Quality: Digital Cytopathology.Journal of pathology informatics · 2018Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
contextThe quality of images produced by whole slide imaging (WSI) scanners has a direct influence on the readers' performance and reliability of the clinical diagnosis. Therefore, WSI scanners should produce not only high quality but also consistent quality images.
aimWe aim to evaluate reproducibility of WSI scanners based on the quality of images produced over time and among multiple scanners. The evaluation is independent of content or context of test specimen.
methodsThe ultimate judge of image quality is a pathologist, however, subjective evaluations are heavily influenced by the complexity of a case and subtle variations introduced by a scanner can be easily overlooked. Therefore, we employed a quantitative image quality assessment method based on clinically relevant parameters, such as sharpness and brightness, acquired in a survey of pathologists. The acceptable level of quality per parameter was determined in a subjective study. The evaluation of scanner reproducibility was conducted with Philips Ultra-Fast Scanners. A set of 36 HercepTest™ slides were used in three sub-studies addressing variations due to systems and time, producing 8640 test images for evaluation.
resultsThe results showed that the majority of images in all the sub-studies are within the acceptable quality level; however, some scanners produce higher quality images more often than others. The results are independent of case types, and they match our perception of quality.
conclusionThe quantitative image quality assessment method was successfully applied in the HercepTest™ slides to evaluate WSI scanner reproducibility. The proposed method is generic and applicable to any other types of slide stains and scanners.
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